To overcome the challenge of balancing high performance with low manufacturing cost in large-aperture compact antenna test range (CATR) systems, this letter proposes and validates a novel linear array feed parabolic cylindrical CATR based on a dimension-separation diffraction control strategy. This strategy decouples the complex two-dimensional edge diffraction problem into two independent one-dimensional problems. In the vertical dimension, passive suppression of edge diffraction is achieved by designing mechanical serrations on the upper and lower edges of the reflector. In the horizontal dimension, this letter proposes an active diffraction cancellation algorithm that controls the quiet zone ripple caused by the straight-cut edges by optimizing the complex excitations of the feed array, eliminating the need for physical serrations. This design concept ensures a high-quality quiet zone, characterized by peak-to-peak amplitude and phase variations of less than 1 dB and 10 degrees, respectively. Simultaneously, it simplifies the reflector manufacturing process and significantly improves aperture efficiency. The proposed CATR demonstrates an exceptional aperture efficiency of up to 91% at 10 GHz. Even at a lower frequency of 2.6 GHz, despite more pronounced diffraction effects from a smaller electrical aperture, it maintains an efficiency of 78.5%. This significantly outperforms both traditional CATR (50%) and fully serrated edge designs with tapering excitation (67.5%).

Localization is expected to support advanced location-aware services in the beyond fifth/sixth-generation (B5G/6G) wireless networks. Conventional methods typically rely on wideband or multiantenna systems to extract delay or spatial features, which are infeasible for low-complexity, narrowband devices that report only received power. The advent of reconfigurable intelligent surfaces (RISs) enables the intelligent yet energy- and hardware-efficient reflection of the feeding signal with controllable reflection phase shifts via software, making high-accuracy positioning and extended service coverage possible. Unlike existing RIS-based localization methods relying on wideband complex signals, this article introduces a novel two-stage method for narrowband power-only localization leveraging two or more distributed RISs. The first stage comprises the initial Tx-RIS-Rx response estimation via power-only fast calibration based on the rotating element electric field vector (REV) method, followed by the RIS-Rx channel response reconstruction. In the second stage, with the obtained RIS-Rx channel response, the multiple signal classification (MUSIC)-based estimation can be performed to first estimate the angle of departures (AoDs) with respect to multidistributed RISs, and then the Rx position is estimated via intersection search. The estimation root-mean-square error (RMSE) versus received signal-to-noise ratio (SNR) was simulated to demonstrate the accuracy and effectiveness of the proposed algorithm in practical low-SNR environments. Benchmarked by the existing RIS beam-searching method, the proposed localization method is experimentally validated for 12 Rx positions by utilizing a 2-bit RIS-assisted measurement system. The measurement results demonstrate that the proposed method offers high-precision localization in narrowband power-only regimes, making it preferred in scenarios that require a fast response and low computational load compared with the conventional wideband complex-signal-based methods.

By utilizing the downlink signal for channel sounding purpose, passive channel sounding has been regraded as a crucial method to investigate the channel characteristics of realistic communication network. In the 5G fifth generation (5G) network, the emitted downlink signals have been steered by the implemented beams of 5G base station (BS). However, the stateof-the-art passive channel sounding campaign in 5G network ignores the effect of BS beams on the radio channel. This paper conducts a multi-beam channel measurement for the live 5G network with the proposed passive channel sounder. The channel measurement campaign is performed under a typical city street scenario along a 138 m route, containing both the line of sight (LOS) and non line of sight (NLOS) scenarios. The multipath parameters in the deployed network, including angular, delay and power profiles, have been thoroughly resolved and analyzed. The measurement results indicate that BS beam effect has a considerable influence on the recorded radio channel in 5G network.

Accurate radar-cross-section (RCS) characterization of unmanned aerial vehicles (UAVs), human heads, and combined human head-hand targets is essential for integrated sensing and communication (ISAC) channel modeling. We therefore conduct monostatic RCS measurements over 0–360° azimuth in an anechoic chamber and derive statistical models for these targets. The measured RCS data are fitted using Rician, Gamma, and LogNormal distributions. Our analysis reveals that the Rician distribution is suitable for modeling small UAV RCS, while the Gamma distribution shows superiority for human head and combined human head-hand targets. Detailed distribution parameters are provided, offering valuable insights for predicting and evaluating the sensing performance of ISAC systems. These findings contribute to advancing ISAC channel research and practical applications.

Field transformation is an established near-field (NF) antenna measurement solution to reconstruct far-field (FF) antenna patterns with high accuracy and hence has been widely adopted. However, it suffers from long measurement time due to the requirement of collecting massive amounts of complex NF data over a closed sphere. The single-cut concept, which can reconstruct the key information of the device under test (DUT) based on the NF data measured on a specific cut, has been introduced to improve the efficiency. This communication proposes a power-only single-cut algorithm based on the spherical wave expansion (SWE), eliminating the requirement of phase measurement. The focus of our work is to determine the key parameters of the single-cut NF multiprobe setup based on power-only measurements, that is, the measurement distances, the probe angular spacing, and the probe angular range. The proposed algorithm along with the cost-effective multiprobe setup is validated through numerical simulations and experimental measurements, providing a highly efficient antenna testing solution for 5G and future antenna systems.

Map-free indoor localization methods can achieve localization purpose without a prior environmental map, thus attracting great interest in recent years. However, existing radio-based methods suffer from degraded localization accuracy in reflective non-line-of-sight (NLoS) environments. In this paper, we exploit the multipath spatial consistency to develop a novel map-free radio indoor localization method. This method first constructs the map using spatial similarities among NLoS paths at nearby known points, and then performs localization using the re-constructed map and the target NLoS components. Specifically, the proposed method consists of two stages: map-construction stage and target-localization stage. In the map-construction stage, first, given the angle-delay profile at a few known points (i.e., training points) within a specific region, the NLoS paths among all training points exhibiting spatial similarities are clustered; Then, the object associated with NLoS path cluster (i.e., shared object) is marked; Next, the non-convex problem of estimating locations of shared objects is formulated, and an efficient iterative convex optimization (ICO)-based algorithm is proposed to obtain the sub-optimal solution; Finally, the estimated results are used to construct the coarse map (i.e., a map that includes shared object locations without specific dimensions). In the target-localization stage, given the re-constructed map and angle-delay profile at an unknown point (i.e., target point), the shared objects interacting with the target point are identified. The proposed ICO-based algorithm is then applied to solve the formulated non-convex problem of estimating the target location. The performance of our proposed method is validated through both radio propagation simulations and measurements, demonstrating promising localization performance in highly reflective environments.

Integrated Sensing and Communication (ISAC) has emerged as a key technology for 6G wireless systems. Channel sounding plays a critical role for system design and development by providing real world channel data required to develop and validate realistic ISAC channel models. Among various channel sounder designs, vector network analyzer (VNA)-based systems are attractive for their scalable frequency and bandwidth configurations, high dynamic-range, and easy accessibility. However, conventional VNA-based sounders lack support for user-defined waveforms, and their inherent frequency-tone operations limit applicability in many ISAC scenarios. This paper presents a novel and flexible modulated VNA-based channel sounder framework that extends the capabilities of conventional VNA-based sounders to support two operating modes: (i) a frequency tone sweeping mode, enabling high accuracy, flexible frequency configuration, scalable bandwidth, and high dynamic-range measurements in the frequency domain; and (ii) a modulated waveform mode, enabling high speed, user-defined waveform measurements in the time domain. A multi-receiver design further enables flexible link configurations, supporting monostatic, bistatic, and multistatic ISAC scenarios. The sounder’s performance is preliminarily validated through static field measurements at 7.2 GHz with 160 MHz bandwidth using three types of waveforms. The measurements fall within the frequency range 3 (FR3), one of the new frequency spectrum for 6G systems. The agreement between the measured multipath components and the known scenario geometries across different links and waveforms confirms the capability and reliability of the proposed sounder framework for realistic ISAC channel measurements under static scenarios, while dynamic measurement campaigns remain a subject of future validation.

Massive multiple-input-multiple-output (MIMO) and millimeter-wave (mmWave) technologies leverage abundant spectrum and large antenna arrays with beamforming capabilities to overcome high propagation loss in sparse channels and enable high data rate wireless communications. However, the increased antenna aperture shifts electromagnetic propagation from the conventional far-field region into the near-field region, leading to performance degradation of traditional codebooks based on the far-field plane wave assumption. Meanwhile, wideband transmission in mmWave systems introduces a spatial-wideband effect that degrades the performance of traditional narrowband-based codebooks. In this communication, we propose a novel distance-frequency-invariant codebook, using mode excitation techniques to compensate for both near-field and wideband effects. For experimental validation, we conducted a measurement campaign in a hall with 20 users using an mmWave massive MIMO system. The results show that near-optimal rates can be achieved through beam training with low training overhead and no additional hardware cost. The proposed beam training framework can be directly implemented in mmWave massive MIMO systems to enhance beam management performance.

Reconfigurable intelligent surface (RIS) has emerged as a pivotal technology for dynamically manipulating electromagnetic wave propagation through software-defined control of passive reflecting elements. Extraction of cascaded channel response for individual elements, which aims to acquire the cascaded channel response between Tx-RIS element-Rx for all elements, which is essential to ensure RIS to operate as intended, such as enabling new applications in sensing, communication and localization. This letter presents a novel, over-the-air method for extracting cascaded channel response that relies solely on amplitude measurements, which requires only two phase states (0$^\circ$ and 180$^\circ$). Specifically, the proposed method constructs a pairwise matrix from power measurements. Subsequently, an alternating optimization algorithm is employed, leveraging spectral relaxation for globally consistent phase estimation and logarithmic least-squares for amplitude estimation. This work provides a practical solution for RIS testing in practical setups, requiring only amplitude measurements.

Semantic radio simultaneous localization and mapping (SR-SLAM), which incorporates landmark material information into conventional R-SLAM, is promising for distributed antenna system (DAS)-based sensing and localization. However, existing methods ignore the geometric constraints induced by multipath spatial consistency across adjacent locations, which provide additional degrees of freedom for reliable path classification and improved SLAM accuracy and robustness. This paper exploits spatial consistency to develop a robust SR-SLAM framework for localization, mapping, and landmark feature extraction under mixed line-of-sight (LoS) and non-LoS (NLoS) conditions. Specifically, a multipath component distance-based algorithm groups paths with similar spatial characteristics. Based on the resulting groups, the LoS group is identified using the minimum-delay criterion and free-space path loss model, while first- and second-order NLoS groups are classified using cost functions derived from their reflection-order geometric relationships. Next, two joint optimization problems are formulated to estimate target locations, reflecting surfaces, and interaction points, and an iterative convex optimization-based algorithm is developed to solve the resulting non-convex problems. Landmark material properties are then inferred by matching measured and modeled path powers. The framework is validated through raytracing simulations and real-world measurements. The results show localization and mapping accuracies of 0.04 m and 0.033 m in simulations, and 0.24 m and 0.135 m in measurements, respectively. The extracted landmark features are consistent with the ground truth in simulations and largely consistent in measurements. Importantly, the framework targets high-frequency DAS scenarios dominated by resolvable LoS and low-order specular reflections, while remaining extendable to higher-order reflected, diffracted, and scattered paths.

Array calibration is critical to achieving accurate beamforming in millimeter-wave (mmWave) antenna-in-package (AiP) phased arrays, where over-the-air (OTA) calibration in ALL-ON mode is a standard requirement. For practical calibration measurements, two core metrics are paramount: efficiency (defined by measurement time) and reliability (robustness, governed by the condition number of the phased array calibration codebook). In this work, we propose a neural network-enabled codebook generation method for phased array calibration compatible with arrays of arbitrary sizes. Codebooks generated via the proposed method achieve low condition numbers while requiring the minimum number of measurements, outperforming state-of-the-art calibration approaches. Practical measurements on a 26-GHz AiP phased array validate the effectiveness and robustness of the proposed method, with superior performance in both array calibration accuracy and beamforming quality.

Pattern synthesis plays a crucial role in antenna array design, enabling the realization of desired radiation patterns that are essential in modern communication. Extremely large-scale antenna arrays (ELAAs) have attracted considerable attention for next-generation wireless communications. However, their practical implementation is hindered by complex and costly architectures involving numerous antenna elements and associated radio frequency chains. The multiplicative array (MA), a well-established concept in pattern synthesis, can achieve a radiation pattern identical to that of a uniform rectangular array (URA) while using significantly fewer antenna elements. In this work, we first review the principle of the novel introduced half-aperture MA (HMA), which has been proposed in our previous work. Then, discuss its performance in the both far field and near field, which is lacking in the previous work. This innovation shows great potential for future research and implementation in large-scale array systems.

Multi-dimensional multipath parameter estimation is essential for characterizing wireless channels. As the system bandwidth and array size increase for 6G communication and sensing systems, the assumption of independence among different channel parameter dimensions no longer holds, which inevitably necessitates multi-dimensional joint parameter search. Moreover, the improved resolution in delay and spatial domains due to ultra-wideband system bandwidth and large array aperture will further increase the computational burden. In this letter, we propose a machine-learning-assisted maximum likelihood estimation (MLE) approach to tackle this critical problem. The proposed method avoids exhaustive dense-grid evaluation in the state-of-the-art MLE algorithms, significantly reducing the complexity and computational burden. Simulation results demonstrate the effectiveness of the proposed method, and an indoor ultra-wideband large-scale channel measurement campaign is further conducted to validate its practical performance.

Currently, there is a great demand for compact anechoic chambers for the purpose of saving construction space and cost. To reduce environmental scattering, anechoic chambers should be equipped with electromagnetic absorbers. Traditional pyramidal absorbers are widely adopted in anechoic chambers for antenna testing. However, the performance of the pyramidal absorbers with compact size is poor in the low-frequency region, making them inappropriate for use in compact anechoic chambers for cellular frequency bands. Meanwhile, the reflection of electromagnetic absorbers made of frequency-selective surfaces (FSSs) can achieve only around -10 dB over a wide frequency band, which is insufficient for antenna testing. In this work, a novel hybrid absorber design framework is reported, which aims to achieve compact absorber design while meeting the demanding requirements of supporting broad bandwidth in the cellular frequency bands and oblique incident angles. The basic idea is to combine the pyramidal absorber with the designed FSS, forming a hybrid absorber with good performance over a broad frequency band. Two types of FSSs operating in the low-frequency region are designed, and then combined with the pyramidal absorber with 10-cm height to achieve good performance over 1-7 GHz, outperforming state-of-the-art designs for this specific frequency band. The hybrid absorber design framework is validated through both numerical simulations and experimental measurements.

In this work, we propose an over-the-air emulation method for dynamic spatial channels that enables efficient evaluation of adaptive antenna systems using a cost-effective wireless cable solution. Unlike conventional wireless cable techniques that necessitate the number of radio frequency (RF) interface ports in the channel emulator to equal the number of antenna elements for the devices-under-test (DUT), the proposed approach scales the required RF ports with the limited number of dominant multipath components present in the channel model. This approach demonstrates particular effectiveness for emulating the increasingly sparse and specular propagation channels characteristic of higher frequency bands, where the spatial filtering inherent in massive antenna beamforming further accentuates channel sparsity. Consequently, the number of dominant propagation paths becomes substantially smaller than the antenna count. To validate the effectiveness of the proposed method, experimental evaluations were conducted using both analog and digital beamforming DUT to estimate the emulated wideband dynamic spatial channel characteristics. The experimental results demonstrate that the proposed method accurately reproduces the per-path power, delay, and angles of arrival of all paths in the target wideband spatial channel at each snapshot.

Indoor localization has gained significant interest from industry and academia in recent years, due to a wide range of location-aware applications. However, most state-of-the-art radio positioning techniques depend heavily on abundant radio channel resources—such as large bandwidth and extensive antenna array aperture, to achieve high spatial and delay resolution in multipath extraction—which are often impractical in real-world deployments. This letter introduces a novel map-based approach that overcomes this limitation by actively integrating indoor environment geometry into signal processing. Low-resolution multipath components (MPCs) obtained under constrained resources are actively validated and refined using map-derived virtual target and specular reflections, filtering out spurious paths that conventional methods cannot resolve. The refined, high-confidence MPCs are then fused to achieve centimeter-level localization accuracy, even with minimal radio channel resources. Experiments using a bandwidth of 200 MHz and 20 antenna elements achieve localization errors of 5.1 cm in line-of-sight and 16.8 cm in obstructed-line-of-sight scenarios, respectively. Compared with state-of-the-art benchmark schemes used a bandwidth of 2 GHz and 720 antenna elements, the proposed framework achieves smaller errors while requiring significantly fewer resources, demonstrating a resource-efficient, geometry-aware pathway for indoor localization.

Over-the-air (OTA) radiated evaluation of integrated wireless devices requires a controlled test field within a limited chamber volume. For many practical devices under test, a square or rectangular footprint is more representative than a circular quiet-zone definition. This paper presents a compact square-quiet-zone field generator based on a ring-distributed single transmitarray and a quiet-zone-oriented synthesis method. The transmitted aperture is modeled using Huygens equivalent sources, and the phase distribution is optimized directly from the amplitude and phase uniformity requirements over the target square test region. A ring-based aperture parameterization and a unified oblique-incidence compensation scheme are adopted to reduce the optimization dimensionality and enable practical phase-only implementation. A prototype operating from 2.5 to 2.7 GHz is fabricated and measured. With an effective aperture of 501.7 mm × 501.7 mm, the prototype generates a 260 mm × 260 mm square quasi-plane-wave test region at a feed-to-quiet-zone distance of 750 mm. The measured amplitude/phase peak-to-peak errors are 2.1 dB/25° at 2.5 GHz, 1.9 dB/16° at 2.6 GHz, and 2.6 dB/22° at 2.7 GHz. The results indicate the feasibility of a compact square-footprint field-generation approach for engineering OTA radiated testing, providing a tradeoff among usable test-region size, feed-to-quiet-zone distance, and single-transmitarray implementation complexity.

Accurate channel models are crucial for the highfrequency systems, including those in the millimeter-wave (mmWave) and terahertz (THz) bands. High-frequency channels exhibit high propagation loss, sparsity, and near-field effects in massive MIMO systems, making deterministic ray-tracing (RT) well-suited for modeling. While RT for high-frequency modeling is widely discussed, its real-world performance requires further investigation. In this article, two measurements at 28 and 100 GHz are used to evaluate the implementation performance of RT in massive MIMO mmwave and THz scenarios. At both frequencies, dominant propagation paths and near-field characteristics are accurately modeled, although several paths in the mmWave band are not reproduced, indicating higher reliability of RT in THz modeling. Furthermore, extensive 300 GHz measurements across 12 locations enable in-depth THz channel characterization. This analysis is based on extensive channel data from 30 locations (12 measured and 18 RT-simulated). These results provides insights for future high-frequency channel modeling and standardization.

Hybrid precoding, as a compromise between low power yet less flexible analog precoding and power hungry but fully flexible digital precoding solutions, has attracted huge attention from industry and academia in recent years for milimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems. The adoption of uniform circular arrays (UCA) can provide advantages of a wide angle scanning range and flat array gain, hence considered for massive MIMO hybrid precoding. However, the phase shifters used in hybrid precoder architectures are typically narrowband, which do not support the ultra- wideband bandwidth required in mmWave systems. This limitation can significantly degrade the performance of UCA in ultra- wideband communications, leading to well-known beam defocus effect. In this paper, we first reveal the beam defocus effects in ultra- wideband mmWave UCA precoding systems, where the beamforming gain severely degrades as the frequency deviates from the center. We then propose a novel frequency-invariant precoder to mitigate beam defocus effect in the hybrid precoding architectures, which approximately achieve the same high beamforming gain for the whole wide bandwidth without extra hardware cost. Finally, numerical simulation and outdoors experimental validations with same parameter settings are performed. Both simulation and measurement results are provided to demonstrate the effectiveness and robustness of the proposed frequency-invariant precoding algorithm.

The transition to near-field (NF) communications in ultra-massive multiple-input multiple-output (UM-MIMO) systems fundamentally alters the spatial degrees of freedom (DoF) of wireless channels. While the NF DoF of line-of-sight (LoS) transmission channels is well-characterized in the literature, the DoF in NF multipath scenarios remains underexplored. This paper investigates the spatial DoF of NF UM-MIMO channels under practical multipath conditions. A generic DoF metric is derived by modeling multipath propagation and analyzing the resulting eigenvalue distribution based on the Green' s function representation of the channel. The DoF contribution of each path is determined by the product of the effective electrical aperture and the subtended solid angle, and the total DoF is obtained through the effective union of spatially resolvable path contributions. A mapping between the eigenvalue distribution and multipath powers is further established. Numerical simulations and real-world NF channel measurements at 28-30 GHz with 720 array elements are conducted for validation in both LoS multipath and non-LoS scenarios. The results show that multipath propagation can significantly increase the spatial DoF and that the proposed metric accurately predicts the DoF of practical NF channels. The proposed framework provides a practical tool for DoF prediction and supports capacity analysis and spatial multiplexing design in future NF UM-MIMO systems.