Terahertz (THz) enables promising Tbps-level wireless transmission thanks to its prospect of ultra-huge spectrum utilization and narrow beamforming in the next sixth-generation (6G) communication system. Compared to millimeter wave (mmWave), THz intrinsically possesses compellingly severer molecular absorption and high pathloss serving confined coverage area. These defects should be well conquered under the employment of ultra-thin 3D beamforming with enormous deployed antennas with high beam gains. However, pencil-beams require substantially high overhead of time and power to train its optimal THz beamforming direction. We propose an energy efficient (EE) oriented THz beamforming (EETBF) scheme by separating the original complex problem into beamforming training (EETBF-BT) acquirement and learning-enabled training power assignment (EETBF-PA). The historical beam data is employed to update next beam selection policy. The performance results have demonstrated that the proposed EETBF outperforms the existing benchmarks leveraging full beam search, iterative search, linear/binary search as well as non-power-control based mechanism in open literature. Our proposed EETBF scheme results in the lowest training latency and power consumption, achieving the highest effective rate and EE performance.

翻译：太赫兹(THz)通信凭借其超高频谱利用率和窄波束成形的前景，在第六代(6G)通信系统中展现出实现Tbps级无线传输的潜力。与毫米波相比，太赫兹波本质上存在更显著的分子吸收效应和高路径损耗，仅适用于有限覆盖区域。这些缺陷需通过部署大规模天线阵列、采用具有高波束增益的超精细三维波束成形技术来有效克服。然而，针状波束需要极高的时间和功率开销来训练其最优太赫兹波束方向。本文提出一种面向能量高效(EE)的太赫兹波束成形(EETBF)方案，将原始复杂问题分解为波束成形训练(EETBF-BT)获取和学习驱动的训练功率分配(EETBF-PA)两个子问题。该方案利用历史波束数据更新下一阶段的波束选择策略。性能结果表明：相较于现有文献中采用全波束搜索、迭代搜索、线性/二分搜索以及非功率控制机制的基准方案，所提出的EETBF方案在训练时延与功耗方面达到最低水平，同时实现了最高的有效速率和能量效率性能。