An active-sensing-based learning algorithm is proposed to solve the near-field beam alignment problem with the aid of wavenumber-domain transform matrices (WTMs). Specifically, WTMs can transform the antenna-domain channel into a sparse representation in the wavenumber domain. The dimensions of WTMs can be further reduced by exploiting the dominance of line-of-sight (LoS) links. By employing these lower-dimensional WTMs as mapping functions, the active-sensing-based algorithm is executed in the wavenumber domain, resulting in an acceleration of convergence. Compared with the codebook-based beam alignment methods, the proposed method finds the optimal beam pair in a ping-pong fashion, thus avoiding high training overheads caused by beam sweeping. Finally, the numerical results validate the effectiveness of the proposed method.

翻译：提出了一种基于主动感知的学习算法，借助波数域变换矩阵(WTM)解决近场波束对准问题。具体而言，WTM能够将天线域信道转换为波数域的稀疏表示。通过利用视距(LoS)链路的主导性，可进一步降低WTM的维度。将这些低维WTM作为映射函数，在波数域中执行主动感知算法，从而加速收敛。与基于码本的波束对准方法相比，所提方法以乒乓方式寻找最优波束对，避免了波束扫描导致的过高训练开销。最后，数值结果验证了所提方法的有效性。