An ultra-broadband angular-stable reflective linear to cross polarization converter based on metasurface is developed. The unit cell of the converter is formed by a slant end-loaded H-shaped resonator. The slant arrangement is to create polarization conversion. The end-loaded stubs are useful for miniaturization and the slots are responsible for enlarging bandwidth. The simulated results show that the polarization conversion ratio of the proposed design is better than 90% in the range of 9.83–29.37 GHz, corresponding to a relative bandwidth of 99.69%. It is also demonstrated that the mean polarization conversion ratio is larger than 80% even though the incident angle reaches 40° for both x-polarized and y-polarized incidences. To validate the design, a prototype of the proposed structure is fabricated and measured. Satisfactory agreement has been observed between measurement and simulation. Compared with the designs in the literature, the developed converter exhibits good performance of high efficiency, ultra-broadband and angular stability. Potential applications can be expected in polarization-controlled devices, stealth surfaces, antennas, etc.

Accurate channel estimation is crucial for millimeter-wave (mmWave) multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Conventional grid-based compressive sensing approaches encounter the base mismatch problem, which degrades channel estimation accuracy. To address this issue, this paper proposes a novel gridless channel estimation strategy tailored for mmWave MIMO-OFDM systems. Specifically, the channel estimation problem is formulated as a joint sparse signal recovery problem by exploiting the inherent sparsity in the angle-delay domain of the mmWave channel. We then introduce a Hankel-Toeplitz block model-based new atomic norm minimization (NANM) algorithm with multiple measurement vectors (MMV), representing the formulated problem as a semi-definite programming (SDP) problem with structured sparsity. To efficiently solve the SDP problem, we employ a low-complexity alternating direction multiplier method (ADMM). Simulation results verify that the proposed method significantly enhances channel estimation accuracy with reduced pilot overhead, compared with conventional channel estimation techniques.

This paper investigates an intelligent reflecting surface (IRS)-aided millimeter wave multiple-input multiple-output system with discrete phase shifters (PSs). To maximize the spectral efficiency, we jointly optimize the hybrid precoder/combiner at the transceiver and the reflecting beamforming at the IRS. Specifically, we propose a cross-entropy (CE)-based probability-learning (CEPL) algorithm to design the reflecting beamforming with 1-bit resolution PSs. In this process, the probability distributions of reflection coefficients are refined by minimizing the CE until they converge to a stable state, in which a near-optimal solution with a sufficiently high probability can be achieved. Then, we extend the CEPL algorithm to a high-resolution PS case for enhancing its effectiveness. After that, the hybrid precoder/combiner is designed by a phase pursuit method. Simulation results show that our proposed scheme significantly performs better than the existing schemes under the discrete PS scenario.

Herein a dual-band wide-angle reflective circular polarization converter, based on a metasurface was developed. The unit cell is composed of a split square ring and a nested square patch. The split square ring plays the role of creating polarization conversion. The square patch is useful for improving the quality of axial ratio. It was verified that the structure could transform the x-polarized incident wave into left-hand circular polarization in the lower frequency band, and to right-hand circular polarization in the higher frequency band. For y-polarized incidence, the transformation has orthogonal modes to that for x-polarized incidence. Moreover, the 3 dB axial ratio takes place in the ranges of 8.42–12.32 GHz and 18.74–29.73 GHz, corresponding to a relative bandwidth of 37.61%, and 45.35%, respectively. In addition, the polarization conversion efficiency is greater than 99% in the ranges of 8.65–11.83 GHz and 19.55–29.36 GHz. Furthermore, for oblique incidence, the axial ratio remains stable, even at 50° incidence, for the lower frequency band. Lastly, a prototype is fabricated and measured for experimental verification. The measured and simulated results were in good agreement. Compared with other designs in the literature, the proposed converter operates with good performance in dual-band, with high-efficiency, and with angular stability.

Terahertz (THz) communication is regarded as a promising technology for future 6G networks because of its advances in providing a bandwidth that is orders of magnitude wider than current wireless networks. However, the large bandwidth and the large number of antennas in THz massive multiple-input multiple-output (MIMO) systems induce a pronounced beam split effect, leading to a serious array gain loss. To mitigate the beam split effect, this paper considers a delay-phase precoding (DPP) architecture in which a true-time-delay (TTD) network is introduced between radio-frequency (RF) chains and phase shifters (PSs) in the standard hybrid precoding architecture. Then, we propose a fast Riemannian conjugate gradient optimization-based alternating minimization (FRCG-AltMin) algorithm to jointly optimize the digital precoding, analog precoding, and delay matrix, aiming to maximize the spectral efficiency. Different from the existing method, which solves an approximated version of the analog precoding design problem, we adopt an FRCG method to deal with the original problem directly. Simulation results demonstrate that our proposed algorithm can improve the spectral efficiency, and achieve superior performance over the existing algorithm for wideband THz massive MIMO systems with angular spread.