Terahertz (THz) communications have been envisioned as a promising enabler to provide ultra-high data transmission for sixth generation (6G) wireless networks. To tackle the blockage vulnerability brought by severe attenuation and poor diffraction of THz waves, a nanoscale reconfigurable intelligent surface (NRIS) is developed to smartly manipulate the propagation directions of incident THz waves. In this paper, the electric properties of the graphene are investigated by revealing the relationship between conductivity and applied voltages, and then an efficient hardware structure of electrically-controlled NRIS is designed based on Fabry-Perot resonance model. Particularly, the phase response of NRIS can be programmed up to 306.82 degrees. To analyze the hardware performance, we jointly design the passive and active beamforming for NRIS aided THz communication system. Particularly, an adaptive gradient descent (A-GD) algorithm is developed to optimize the phase shift matrix of NRIS by dynamically updating the step size during the iterative process. Finally, numerical results demonstrate the effectiveness of our designed hardware architecture as well as the developed algorithm.

翻译：Terahertz (THZ) 通信被认为是为第六代(6G)无线网络提供超高数据传输的极高数据传输的有希望的推进器。为了应对因严重减速和低度分解THZ波造成的阻塞性脆弱性,我们开发了纳米的可重新配置智能表面,以便明智地操纵事件THZ波的传播方向。在本文中,通过披露导电率与应用电压之间的关系,对石墨的电子特性进行了调查,然后根据Fabry-Perot Resonance模型设计了一个由电力控制的NRIS高效硬件结构。特别是,NRIS的阶段反应可编程到306.82度。为了分析硬件性能,我们联合设计了NRIS辅助THZ通信系统的被动和主动成型。特别是,正在开发一个适应性梯度下降(A-GD)算法,以优化NRIS的阶段转移矩阵,在迭接过程中动态更新步骤尺寸。最后,数字结果表明我们设计的硬件结构作为发达的算法的有效性。