This paper studies an intelligent reflecting surface (IRS)-aided multi-antenna simultaneous wireless information and power transfer (SWIPT) system where an $M$-antenna access point (AP) serves $K$ single-antenna information users (IUs) and $J$ single-antenna energy users (EUs) with the aid of an IRS with phase errors. We explicitly concentrate on overloaded scenarios where $K + J > M$ and $K \geq M$. Our goal is to maximize the minimum throughput among all the IUs by optimizing the allocation of resources (including time, transmit beamforming at the AP, and reflect beamforming at the IRS), while guaranteeing the minimum amount of harvested energy at each EU. Towards this goal, we propose two user grouping (UG) schemes, namely, the non-overlapping UG scheme and the overlapping UG scheme, where the difference lies in whether identical IUs can exist in multiple groups. Different IU groups are served in orthogonal time dimensions, while the IUs in the same group are served simultaneously with all the EUs via spatial multiplexing. The two problems corresponding to the two UG schemes are mixed-integer non-convex optimization problems and difficult to solve optimally. We propose efficient algorithms for these two problems based on the big-M formulation, the penalty method, the block coordinate descent, and the successive convex approximation. Simulation results show that: 1) the non-robust counterparts of the proposed robust designs are unsuitable for practical IRS-aided SWIPT systems with phase errors since the energy harvesting constraints cannot be satisfied; 2) the proposed UG strategies can significantly improve the max-min throughput over the benchmark schemes without UG or adopting random UG; 3) the overlapping UG scheme performs much better than its non-overlapping counterpart when the absolute difference between $K$ and $M$ is small and the EH constraints are not stringent.

翻译：本文研究了一种智能反射面（IRS）辅助的多天线同步无线信息与功率传输（SWIPT）系统，其中拥有$M$根天线的接入点（AP）借助存在相位误差的IRS，为$K$个单天线信息用户（IU）和$J$个单天线能量用户（EU）提供服务。我们重点考虑$K + J > M$且$K \geq M$的过载场景。目标是通过优化资源分配（包括时间、AP端发射波束成形以及IRS端反射波束成形），在保证每个EU最小收获能量量的前提下，最大化所有IU中的最小吞吐量。为此，我们提出了两种用户分组（UG）方案，即非重叠UG方案和重叠UG方案，其区别在于多个分组中是否可以存在相同的IU。不同IU组在正交的时间维度上被服务，而同一组内的IU则通过空间复用与所有EU同时被服务。这两种UG方案对应的优化问题均为混合整数非凸优化问题，难以求得最优解。我们基于大M法、罚函数法、块坐标下降法和逐次凸近似法，为这两个问题提出了高效算法。仿真结果表明：1）所提出的鲁棒设计方案的非鲁棒对应版本不适用于存在相位误差的实际IRS辅助SWIPT系统，因为能量收集约束无法满足；2）所提出的UG策略相较于不采用UG或采用随机UG的基准方案，能显著提升最大最小吞吐量；3）当$K$与$M$的绝对差值较小且能量收集约束不严格时，重叠UG方案的性能远优于其非重叠对应方案。