With the development of communication technology has come several measurement applications requiring plane-wave conditions for wireless-device characterizations in anechoic chambers. In this paper, a metasurface lens with a 2 × 2 feeding-antenna array is proposed and characterized to synthesize a plane wave in a near field for a fifth-generation (5G) millimeter-wave radio-frequency (RF) devices test. The metasurface lens, based on Jerusalem-cross elements printed on a printed circuit board (PCB) substrate, is used for controlling the phase-shift distribution of incident spherical waves. The lens has a size of 0.4 × 0.4 m and is designed to operate at a range from 24.25 GHz to 27.5 GHz, and its feeding-antenna array is located at a focal plane of the lens, which is parallel to the metasurface lens. The lens is studied and verified through simulations and experiments, and a uniform amplitude and phase-field distribution at a reduced distance of 1.2 m generated by the metasurface lens throughout a QZ are achieved. The worst-case amplitude and phase variation of the designed metasurface lens are ±0.75 dB and ±7.5°, respectively. The results show a plane-wave condition can be achieved in 5G millimeter bands through the proposed compact and effective metasurface lens. Moreover, the proposed metasurface lens is shown to be capable of reducing the plane-wave synthesizing distance compared to the compact antenna test range (CATR) with a significantly reduced system cost, making it an attractive alternative to antenna testing in 5G millimeter-wave frequency bands.

Tracking multiple targets within a group is a challenging task in the radar field, especially for a bird flock. Targets in a group are usually closely spaced and exhibit similar characteristics. Additionally, the tracking radar typically employs a narrow beam to achieve a high range–angular resolution, resulting in incomplete measurements within the limited beamwidth. These factors lead to false association and track fragmentation in target tracking. However, in addition to kinematic characteristics, birds exhibit temporally correlated micro-Doppler signatures because of their wingbeat behavior, which can be utilized in target tracking. Therefore, this paper proposes an adaptive TPHD tracking method using Doppler features. First, a Doppler temporal contrastive network is designed to learn the micro-Doppler representation for the association of birds. Then, the learned feature is fused with kinematic parameters, using XGBoost to guide the weight update in the filter. Moreover, adaptive mechanisms are incorporated into the TPHD filter to achieve stable tracking under incomplete measurements. Simulation and experimental results verified the effectiveness of the proposed method and showed better tracking performance than the competing method.

An adaptive sampling and optimized extrapolation scheme for spherical near-field antenna testing is proposed. The method relies on the partition clustering classification algorithm and Voronoi classification to divide a small amount of initial data into subclasses and cells. The sampling density and rates of variation between adjacent sampling points are used as an overall metric function to evaluate the sampling dynamics at each location. Appropriate interpolation is performed in the highly dynamic region to increase the effective data in the near-field samples. The Gerchberg-Papoulis algorithm extrapolates the unnecessary interpolation region to improve the near-field sampling accuracy. This method uses a small amount of initial near-field sampled data for near-far field conversion to achieve the same precision as uniform oversampling. The feasibility and stability of the algorithm are proved from the actual measurement results.

Simultaneous wireless information and power transfer (SWIPT) has attracted sustained interest. We propose a null-space-based transmission scheme for multiuser SWIPT serving both energy users (EUs) and information users (IUs). Under a practical nonlinear energy-harvesting (EH) model and multiple waveform options, we revisit the role of dedicated energy beams (EBs). We show that, in general, dedicated EBs are unnecessary because information beams (IBs) with Gaussian signaling can simultaneously support wireless energy transfer (WET) and wireless information transfer (WIT), unless special energy-centric waveforms (e.g., deterministic sinusoidal waveforms) are employed and provide sufficient gains. Guided by these insights, we formulate an optimization problem for EB design to enable dedicated waveform transmission for WET, and we develop a low-complexity algorithm that reduces computation by ignoring the WET contribution of IBs during optimization. Numerical results corroborate that deterministic sinusoidal waveforms outperform Gaussian signaling when the received RF power lies in the EH high-efficiency region, making dedicated EBs beneficial. The proposed scheme achieves computational complexity reductions of 91.43\% and 98.54\% for the cases $M=8,,K^I=K^E=2$ and $M=16,,K^I=K^E=4$, respectively, with negligible performance loss, thereby validating the efficiency of the low-complexity algorithm.