Programmable vanadium dioxide (VO₂) metasurface is proposed at THz frequencies. The insulating and metallic states of VO₂ can be switched via external electrical stimulation, resulting in the dynamical modulation of electromagnetic response. The voltages of different columns of the metasurface can be controlled by the field-programmable gate array, and thus the phase gradients are realized for THz beam steering. In 1-bit coding, we design periodic and nonperiodic 24 × 24 coding sequences, and achieve wide-angle beam scanning with the deflection angles from −60° to +60°. In 2-bit coding, we use two different meta-atoms to design 18 × 18 coding sequences. Compared with 1-bit coding, 2-bit coding has more degree of freedom to control the optical phase, and 3 dB diffraction efficiency is improved by generating a single deflection angle. The proposed programmable metasurfaces provide a promising platform for manipulating electromagnetic wave in 6G wireless communication.

Providing reliable and efficient coverage for cell-edge mobile users (MUs) is a key issue in wireless communication networks. With non-uniform structure and heterogeneity of network topology in the 5G/B5G networks, performance improvement of cell-edge MUs becomes even more challenging. Unmanned aerial vehicle (UAV) exhibits a comparable advantage in enhancing cell edge performance due to its flexible mobility and line-of-sight air-to-ground links. In this paper, we study UAV-assisted cell-edge MU offloading in the non-uniform heterogeneous cellular networks. A base station (BS) coordination and ground-to-air offloading scheme is proposed to enhance the cell-edge MUs’ performance, whereby cell-edge MUs are periodically scheduled between coordinated ground BSs and a flying UAV. Furthermore, a theoretical framework is developed to analyze the average spectral efficiency (SE) and average network throughput. Specifically, closed-form expressions for the average SE are derived for MUs associated with the ground BSs. Upper and lower bounds for the average SE are also obtained when the MU is offloaded to the flying UAV. Finally, numerical and simulation results are provided to validate the theoretical analysis and investigate the impact of key system parameters on the system performance, which also demonstrate the advantages of the UAV-assisted offloading scheme, compared with benchmark solutions.

Fluid antenna multiple access (FAMA) is a new technology that allows mobile devices equipped with a fluid antenna to have a space-division multiple-access (SDMA) capability. In this letter, we investigate the downlink energy efficiency (EE) of the above system. Specifically, the optimal control problem of BS’s transmit power and users’ fluid antenna positions is modeled as a mean-field game (MFG). Results show that the EE using our power control strategy increases as the space of fluid antenna increases and becomes close to the EE of MIMO-SDMA when the space is large.

Terahertz polarization converter has drawn great attention for its properties of wavefront control in recent years. However, the low transmission efficiency of these converters remains a major obstruction to be resolved. A promising solution is the all-dielectric metasurface, based on which, this study proposes a high-efficiency transmissive terahertz linear-to-circular polarization converter. The simulations show the transmission efficiency of the converter is beyond 88% with an ellipticity < −0.8 from 0.555 to 0.737 THz, and the maximum efficiency even reaches 100% at 0.660 THz. Furthermore, the converter can also be actively manipulated by combining with dynamic material. The frequency sensitivity is 98 GHz/100K, and the modulation depth of ellipticity at 0.725 THz exceeds 76%. The excellent performances of these converters offer more potentials for terahertz devices.

Reasonable resource management scheme is the premise to ensure system reliability and practicability of vehicle-to-vehicle (V2V) communications network. In this paper, spectrum resource allocation and power control scheme is studied. Firstly, the problem of resource block (RB) sharing is considered. Assuming that each V2V link occupies at most one resource block while multiple links can share the same RB. In this work, a factor graph model is proposed corresponding to the RB allocation problem through function mapping. Therefore, the RB allocation problem is equivalent to studying the message update and belief inference problem on the factor graph model. We propose a Belief Propagation based on Real-time Update of Messages (BPRUM) algorithm, in which the message of each node is calculated based on the new messages of other nodes rather than the messages calculated in the last iteration. Secondly, after the RB allocation is completed, a power control scheme under the maximum power limit is proposed by utilizing the Lagrange dual decomposition. And the total throughput of the system is maximized by using the proposed power control scheme. Simulation results show that the resource allocation and power control scheme can achieve a significant increment in spectrum utilization and throughput of the V2V communications network.

Intelligent reflecting surfaces (IRSs) have recently attained growing popularity in wireless networks owning to their capability to customize the wireless channel via smartly configured passive reflections. In addition to optimizing IRS reflection patterns, the flexible deployment of IRSs offers another design degree of freedom (DoF) to reconfigure the wireless propagation environment in favour of signal transmission. To unveil the impact of IRS deployment on the system capacity, we investigate the capacity of a broadcast channel with a multi-antenna base station (BS) sending independent messages to multiple users, aided by IRSs with N elements. In particular, both the distributed and centralized IRS deployment architectures are considered. Regarding the distributed IRS , the N IRS elements form multiple IRSs and each of them is installed near a user cluster; while for the centralized IRS, all IRS elements are located in the vicinity of the BS. To draw essential insights, we first derive the maximum capacity achieved by the distributed IRS and centralized IRS , respectively, under the assumption of line-of-sight (LoS) propagation and homogeneous channel setups. By carefully capturing the fundamental tradeoff between the spatial multiplexing gain and passive beamforming gain, we rigourously prove that the capacity of the distributed IRS is higher than that of the centralized IRS provided that the total number of IRS elements is above a threshold. Motivated by the superiority of the distributed IRS , we then focus on the transmission and element allocation design under the distributed IRS . By exploiting the user channel correlation of intra-clusters and inter-clusters, an efficient hybrid multiple access scheme relying on both spatial and time domains is proposed to fully exploit both the passive beamforming gain and spatial DoF. Moreover, the IRS element allocation problem is investigated for the objectives of the sum-rate maximization and the minimum user rate maximization, respectively. Finally, extensive numerical results are provided to validate our theoretical finding and also to unveil the effectiveness of the distributed IRS for improving the system capacity under various system setups.