Beamforming for PIN Diode-Based IRS-Assisted Systems Under a Phase Shift-Dependent Power Consumption Model

TL;DR

The paper addresses rate maximization in IRS-assisted downlink systems under a phase shift-dependent power consumption (PS-DPC) model, introducing a total system power constraint that couples BS and IRS power. It develops a Generalized Benders Decomposition (GBD-BF) approach for the single-user case, alongside a low-complexity S-CSI-based beamforming method that optimizes offline power split and online beamforming. For the multi-user case, two joint power allocation and beamforming strategies (JPABF) are proposed within a WMMSE framework, offering options with optimal- or scaled-beamformers to balance performance and complexity. Simulations show that the proposed methods flexibly allocate power between BS and IRS to maximize rate under PS-DPC, with performance advantages most pronounced at moderate budgets and larger IRS sizes; at high budgets the IRS can be more aggressively used, while at low budgets more power is allocated to the BS. Overall, the work demonstrates practical beamforming designs that account for PS-DPC, enabling more efficient IRS-assisted networks in real deployments.

Abstract

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.

Figures (8)

• Figure 1: System model for an IRS-assisted downlink multi-user MISO system.
• Figure 2: Rate versus $P_{\mathrm{0}}$ for different beamforming methods.
• Figure 3: $P_{\mathrm{IRS,PS}}$ versus $P_{\mathrm{0}}$ for different beamforming methods.
• Figure 4: Rate versus $M$ for different beamforming methods.
• Figure 5: $P_{\mathrm{IRS,PS}}$ versus $M$ for different beamforming methods.

Theorems & Definitions (4)

• Lemma 1
• Lemma 2
• Lemma 3
• Lemma 4