This letter considers an intelligent reflecting surface(IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy from a power station (PS) in the downlink (DL) and then transmit information using non-orthogonal multiple access (NOMA) to a data sink in the uplink (UL). However, most existing works on WPCNs adopted the simplified linear energy-harvesting model and also cannot guarantee strict user quality-of-service requirements. To address these issues, we aim to minimize the total transmit energy consumption at the PS by jointly optimizing the resource allocation and IRS phase shifts over time, subject to the minimum throughput requirements of all devices. The formulated problem is decomposed into two subproblems, and solved iteratively in an alternative manner by employing difference of convex functions programming, successive convex approximation, and penalty-based algorithm. Numerical results demonstrate the significant performance gains achieved by the proposed algorithm over benchmark schemes and reveal the benefits of integrating IRS into WPCNs. In particular, employing different IRS phase shifts over UL and DL outperforms the case with static IRS beamforming.

中文翻译：

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利用非线性能量收集模型实现 IRS 辅助 WPCN 的能量最小化


这封信考虑了智能反射表面 (IRS) 辅助的无线供电通信网络 (WPCN)，其中设备首先从下行链路 (DL) 中的发电站 (PS) 收集能量，然后使用非正交多址 (NOMA) 传输信息）到上行链路（UL）中的数据接收器。然而，现有的WPCN工作大多采用简化的线性能量收集模型，也不能保证严格的用户服务质量要求。为了解决这些问题，我们的目标是在满足所有设备的最低吞吐量要求的前提下，通过联合优化资源分配和随时间推移的 IRS 相移，最大限度地减少 PS 的总传输能耗。将公式化的问题分解为两个子问题，并采用凸函数差分编程、逐次凸逼近和基于惩罚的算法以替代方式迭代求解。数值结果证明了所提出的算法相对于基准方案取得了显着的性能提升，并揭示了将 IRS 集成到 WPCN 中的好处。特别是，在 UL 和 DL 上采用不同的 IRS 相移优于静态 IRS 波束成形的情况。