使用均匀阵列采样与重建角域
Sampling and Reconstructing Angular Domains with Uniform Arrays
AI总结：
针对模拟/混合均匀阵列角域扫描中采样步长与开销的矛盾，本文提出SARA有限采样与无损重建方法，并在目标检测和无线电成像中验证其性能与复杂度优势。
摘要：
无线网络中大规模天线阵列的激增，促使人们采用模拟/混合阵列方案：在这类方案中，多个天线单元由同一个射频前端驱动，以沿特定角度形成波束，从而最大化波束赋形增益。已有许多启发式方法通过在采样步长与开销之间进行权衡来采样角域，而任意小的角度步长只有在无限采样开销下才能实现。我们表明，对于均匀线性阵列和矩形阵列，无需借助角度稀疏性假设，仅使用有限数量的样本，就能够以任意角度精度对阵列的角度响应进行无损重建。所提出的方法“角域采样与重建”（sampling and reconstructing angular domain，SARA）定义了需要采样的角度数量、具体角度以及相应的重建方式。因此，这一扫描角域的通用解决方案不仅可应用于波束获取和信道估计，还可应用于无线电成像技术，使其成为未来通感一体化（integrated sensing and communications，ISAC）的候选方案。针对目标检测和无线电成像的大量仿真结果表明，无论在角度重建性能还是计算复杂度方面，SARA相较所考虑的其他基线都具有明显优势。
英文摘要：
The surge of massive antenna arrays in wireless networks calls for the adoption of analog/hybrid array solutions, where multiple antenna elements are driven by a common radio front end to form a beam along a specific angle in order to maximize the beamforming gain. Many heuristics have been proposed to sample the angular domain by trading off between sampling step size and overhead, where arbitrarily small angular step size is only attainable with infinite sampling overhead. We show that, for uniform linear and rectangular arrays, lossless reconstruction of the array's angular responses at arbitrary angular precision is possible using a finite number of samples without resorting to assumptions of angular sparsity. The proposed method, sampling and reconstructing angular domain (SARA), defines how many and which angles to be sampled and the corresponding reconstruction. This general solution to scan the angular domain can therefore be applied not only to beam acquisition and channel estimation, but also to radio imaging techniques, making it a candidate for future integrated sensing and communications (ISAC). Extensive simulation results for target detection and radio imaging have demonstrated clear advantages of SARA versus other considered baselines, both in terms of angular reconstruction performance and computational complexity.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
