Terahertz (THz) band provides huge bandwidth but the molecular absorptions in these frequencies cause high path losses in long distance communications. Recently, Multi-band Ultra-massive MIMO (UM-MIMO) systems based on graphene-based plasmonic nano-antennas have been proposed to overcome the distance problem. In the UM MIMO systems, the mutual coupling effect is a challenging problem because of the ultra-dense integration of the multi-band nano-antenna arrays. In this paper, a graphene-based frequency selective surface (FSS) is proposed to reduce the coupling effects in dense plasmonic nano-antenna arrays for multi-band UM MIMO systems. The performance of the proposed structure is evaluated by full-wave simulation for different cases. The results show the FSS structure has a wide stop-band (-15 dB bandwidth, approximately 43% to 50%) from 1.1 THz to 1.7 THz. By inserting the FSS structure between nano-antennas, a high isolation coefficient of -25 dB with a 15 dB fall and an envelope correlation coefficient (ECC) less than 0.01 are achieved. The field distributions and the radiation patterns are also presented to confirm that the proposed FSS structure improves the performance of the array with negligible influence on the antenna itself. Moreover, the receiving mode simulation of the array is performed with the FSS structure. It is also asymptotically shown that the mutual coupling experienced by the nano-antenna with the FSS structure is negligible even in the presence of very large number of closely integrated elements. Finally, technological issues are discussed for practical implementations.

The design and implementation of the filters for the fifth-generation (5G) mobile communication systems are challengeable due to the demands of high integration, low-cost, and high-speed data transmission. In this paper, a dual-wideband bandpass filter (BPF) and a tri-wideband BPF for 5G mobile communications are proposed. The dual-wideband BPF consists of two folded open-loop stepped-impedance resonators (FOLSIRs), and the tri-wideband BPF is designed by placing a pair of folded uniform impedance resonator inside the dual-wideband BPF with little increase in the physical size of the filter. By employing a novel structural deformation of a stepped-impedance resonator, the FOLSIR is achieved with a more compact structure, a controllable transmission zero, and an adjustable resonant frequency. The measurement results show that the working bands of the two filters are 1.98–2.28/3.27–3.66 GHz and 2.035–2.305/3.31–3.71/4.54–5.18 GHz, respectively, which are consistent with the full-wave EM simulation results. The implemented filters have a compact size and the results show low loss, good out-of-band rejection, and wide passbands covering sub-6 GHz bands of 5G mobile communications and a commonly used spectrum.

We propose a flexible anti-metal radio frequency identification (RFID) tag antenna based on a high-conductivity graphene assembly film (HCGAF). The HCGAF has a conductivity of 1.82 × 10⁶ S m⁻¹, a sheet resistance of 25 mΩ and a thickness of 22 μm. The HCGAF is endowed with high conductivity comparable to metal materials and superb flexibility, which is suitable for making antennas for microwave frequencies. Through proper structural design, parameter optimization, semiautomatic manufacturing and experimental measurements, an HCGAF antenna could realize a realized gain of –7.3 dBi and a radiation efficiency of 80%, and the tag could achieve a 6.4 m read range at 915 MHz on a 20 × 20 cm² flat copper plate. In the meantime, by utilizing flexible polyethylene (PE) foam, good conformality was obtained. The read ranges of the tags attached to curved copper plates with different bending radii were measured, as well as those of those attached to several daily objects. All the results demonstrate the excellent performance of the design, which is highly favorable for practical RFID anti-metal applications.

The resonance performance analysis of graphene antennas is a challenging problem for full-wave electromagnetic simulators due to the trade-off between the computer resource and the accuracy of results. In this paper, an equivalent circuit model is presented to provide a concise and fast way to analyze the graphene-based THz bowtie antenna. Based on the simulated results of the frequency responses of the antenna, a suitable equivalent circuit of Resistor-Inductor-Capacitor (RLC) series is proposed to describe the antenna. Then the RLC parameters are extracted by considering the graphene bowtie antenna as a one-port resonator. Parametric analyses, including chemical potential, arm length, relaxation time, and substrate thickness, are presented based on the proposed equivalent circuit model. Antenna input resistance R is a significant parameter in this model. Validation is performed by comparing the calculated R values with the ones from full-wave simulation. By applying different parameters to the graphene bowtie antenna, a set of R, L, and C values are obtained and analyzed comprehensively. A very good agreement is observed between the equivalent model and the numerical simulation. This work sheds light on the graphene-based bowtie antenna’s initial design and paves the way for future research and applications.

Using intelligent optimization algorithms to retrieve atmospheric duct parameters by monitoring automatic identification system (AIS) signals at sea is a new passive remote sensing technology for atmospheric ducts. To thoroughly compare and analyze the inversion results of different intelligent optimization algorithms and optimize the parameters of the algorithms, this study considered a simulated atmospheric duct environment for atmospheric duct inversion using the genetic, simulated annealing, and particle swarm optimization (PSO) algorithms. The results indicated that the PSO algorithm exhibited the best inversion performance. The inversion results of the simulated annealing particle swarm optimization (SAPSO) and PSO algorithms under different inversion parameters were further statistically analyzed, and the atmospheric duct parameters were obtained from measured AIS signals based on the SAPSO algorithm. The inversion results verified the effectiveness of the proposed algorithm, and they continuously improved with additional calculations in the inversion algorithm. However, the changing trend gradually slowed. Therefore, in practical applications, the inversion time consumption should be balanced with the inversion effect to optimize the inversion parameters.