Intelligent reflecting surfaces (IRSs) have been regarded as a promising enabler for future wireless communication systems. In the literature, IRSs have been considered power-free or assumed to have constant power consumption. However, recent experimental results have shown that for positive-intrinsic-negative (PIN) diode-based IRSs, the power consumption dynamically changes with the phase shift configuration. This phase shift-dependent power consumption (PS-DPC) introduces a challenging power allocation problem between base station (BS) and IRS. To tackle this issue, in this paper, we investigate a rate maximization problem for IRS-assisted systems under a practical PS-DPC model. For the single-user case, we propose a generalized Benders decomposition-based beamforming method to maximize the achievable rate while satisfying a total system power consumption constraint. Moreover, we propose a low-complexity beamforming design, where the powers allocated to BS and IRS are optimized offline based on statistical channel state information. Furthermore, for the multi-user case, we solve an equivalent weighted mean square error minimization problem with two different joint power allocation and phase shift optimization methods. Simulation results indicate that compared to baseline schemes, our proposed methods can flexibly optimize the power allocation between BS and IRS, thus achieving better performance. The optimized power allocation strategy strongly depends on the system power budget. When the system power budget is high, the PS-DPC is not the dominant factor in the system power consumption, allowing the IRS to turn on as many PIN diodes as needed to achieve high beamforming quality. When the system power budget is limited, however, more power tends to be allocated to the BS to enhance the transmit power, resulting in a lower beamforming quality at the IRS due to the reduced PS-DPC budget.

翻译：智能反射面（IRS）被视为未来无线通信系统的关键使能技术。现有文献通常假设IRS无功耗或具有恒定功耗。然而，近期实验结果表明，对于基于正-本征-负（PIN）二极管的IRS，其功耗会随相移配置动态变化。这种相移依赖功耗（PS-DPC）在基站（BS）与IRS之间引入了具有挑战性的功率分配问题。为应对该问题，本文基于实际PS-DPC模型研究IRS辅助系统的速率最大化问题。针对单用户场景，我们提出一种基于广义Benders分解的波束成形方法，在满足系统总功耗约束的前提下最大化可达速率。此外，我们提出一种低复杂度波束成形设计方案，其中基于统计信道状态信息对基站与IRS的功率分配进行离线优化。进一步地，针对多用户场景，我们通过两种不同的联合功率分配与相移优化方法求解等效加权均方误差最小化问题。仿真结果表明，相较于基线方案，所提方法能够灵活优化基站与IRS间的功率分配，从而获得更优性能。优化后的功率分配策略高度依赖于系统功率预算：当系统功率预算充足时，PS-DPC并非系统功耗的主导因素，IRS可开启所需数量的PIN二极管以实现高质量波束成形；而当系统功率预算受限时，更多功率倾向于分配给基站以增强发射功率，导致IRS可用的PS-DPC预算减少，从而降低其波束成形质量。