Extremely large-scale array (XL-array) has emerged as a promising technology to enhance the spectrum efficiency and spatial resolution in future wireless networks, leading to a fundamental paradigm shift from conventional far-field communications towards the new near-field communications. Different from the existing works that mostly considered simultaneous wireless information and power transfer (SWIPT) in the far field, we consider in this paper a new and practical scenario, called mixed near- and far-field SWIPT, in which energy harvesting (EH) and information decoding (ID) receivers are located in the near- and far-field regions of the XL-array base station (BS), respectively. Specifically, we formulate an optimization problem to maximize the weighted sum-power harvested at all EH receivers by jointly designing the BS beam scheduling and power allocation, under the constraints on the ID sum-rate and BS transmit power. To solve this nonconvex optimization problem, an efficient algorithm is proposed to obtain a suboptimal solution by leveraging the binary variable elimination and successive convex approximation methods. Numerical results demonstrate that our proposed joint design achieves substantial performance gain over other benchmark schemes.

翻译：极大规模阵列（XL-array）已成为未来无线网络中提升频谱效率与空间分辨率的极具前景的技术，这导致传统远场通信向新型近场通信的根本性范式转变。不同于现有研究主要考虑远场场景下的同步无线信息与功率传输（SWIPT），本文考虑一种新颖且实用的混合近场与远场SWIPT场景：其中能量采集（EH）接收机与信息解码（ID）接收机分别位于极大规模阵列基站（BS）的近场区域和远场区域。具体而言，我们构建了一个在ID总速率与BS发射功率约束下，通过联合设计BS波束调度与功率分配来最大化所有EH接收机加权和功率的优化问题。针对该非凸优化问题，本文提出一种高效算法，利用二进制变量消除与逐次凸逼近方法获得次优解。数值结果表明，所提出的联合设计方案相较于其他基准方案实现了显著的性能增益。