This work proposes an element with 1-bit phase resolution that operates in both reflection and radiation modes. The 1-bit phase responses in two operating modes can be realized by switching the states of three integrated PIN diodes. The array composed of the elements can be excited as both a reflectarray (RA) by the external feed in space and a phased array (PA) without phase shifters by the integrated feeding network at its bottom. Drawing inspiration from the RA, the feeding network introduces initial phase distributions irradiated by a hypothetical spatial feed above the PA to mitigate the grating lobes of the 1-bit PA. An electronically reconfigurable array antenna prototype composed of 8 × 16 elements was manufactured and measured to verify its performance. The experimental results indicate that the designed array antenna can realize dynamic beam scanning in the range of ±45° in E-plane and ±30° in H-plane within less than 3 dB gain loss, verifying its feasibility for both RA and PA applications.

In this communication, a novel hybrid decoupler is proposed to reduce mutual coupling for an extremely compact wideband stacked patch MIMO array antenna. The hybrid decoupler consists of a dielectric surface and a metasurface. By using a well-designed dielectric surface, the mode of mutual coupling current on the unexcited antenna can become orthogonal to its polarization mode. Moreover, the electrical distance of coupling wave propagation between two elements is prolonged. Antenna decoupling is naturally achieved. Then, the metasurface, which can reject coupling wave propagation, is a complementary method to further improve isolation. Dielectric rod array is designed by partially hollowing the dielectric surface, which can realize optimized dielectric constant of slab and better combine two decoupling methods. A broadband stacked patch array antenna is chosen as a demonstration to prove that this idea can achieve wide isolation improved bandwidth, as well as high isolation improved degree. Measured results reveal that isolation enhancement ranges from 6 to 21 dB in the frequency band from 1.83 to 2.17 GHz.

In order to improve the efficiency and accuracy of antenna optimization, an adaptive evolutionary neural network (AENN) based optimization design method for wideband dual-polarized antenna is proposed. The proposed AENN is composed of two networks. The first network is used to predict the structural parameters of the antenna, and the second network uses the structural parameters as input to verify the results of the first network. This method only needs a small number of data set to pre-train the network, and then, through the advanced workflow, while updating the data set, the two networks can evolve iteratively, and finally the antenna structural parameters under the expected electromagnetic response can be obtained. Taking two wideband dual-polarized antennas as numerical examples, this method is compared with other advanced antenna optimization methods, and the effectiveness of this method is verified.

A novel wideband and compact water antenna with optically transparent characteristic is presented in this communication. This antenna mainly consists of a fan-shaped cylindrical radiator, a top disk, a cylindrical base, and a water reflector. Based on two resonant modes, this antenna can achieve wideband characteristic. Meanwhile, when combined with fan-shaped radiator and top disk loading, the overall dimensions can be greatly reduced without compromising impedance matching. The ground made of distilled water is used for full transparency. The proposed antenna covers frequency range from 1.16 to 2.79 GHz for $S_{11} < -10$ dB. As far as we know, the proposed antenna shows the widest relative bandwidth (82.5%) in the field of transparent antennas, without sacrificing size and radiation performance.

This brief demonstrated a body-wide RF energy harvester based on textile spoof surface plasmon (SSP) antenna array for wearable wireless power transmission. This harvester includes four patch antennas and SSP waveguides to form an SSP antenna array integrated with clothing to harvest the incident RF energy. Then, a loop and rectifier are integrated and fabricated in the same plane to extract, combine, rectify and output DC power from the multi-path harvested energy in a contactless way and without a complex matching network. They are fabricated with a simple structure, entirely off-the-shelf flexible and textile materials, and a proven fabrication technique. Finally, it is worn on the body to output DC power of $108.89~\mu \text{W}$ when illuminated with a power density of $7.96~\mu \text{W}$ /cm2 at 2.4-2.45 GHz Industrial Scientific Medical (ISM) band. This design could be applied to power the potential wearable sensors wirelessly.

Channel state information (CSI) is usually estimated by the user equipment (UE) and fed back to the base station (BS). The quality of the CSI received by the BS significantly impacts the performance of large-scale multiple-input-multiple-output (MIMO) system. The CSI feedback consumes a large amount of uplink bandwidth resources, especially in massive MIMO system. Traditional CSI feedback methods cause feedback performance bottlenecks due to their computational error and complexity limitations. In recent years, deep learning (DL)-based CSI feedback methods have made significant progress. However, most of the existing DL-based methods improve CSI feedback performance at the cost of higher computational complexity. In this letter, we introduce the MetaFormer generic lightweight architecture to CSI feedback and design a lightweight feedback model PFNet based on it, which employs pooling operations instead of the attention mechanism in the traditional Transformer architecture, thus significantly reducing the complexity. Experimental results show that PFNet outperforms current lightweight SOTA networks in most scenarios.