Intelligent reflecting surfaces (IRSs) are envisioned as a low-cost solution to achieve high spectral and energy efficiency in future communication systems due to their ability to customize wireless propagation environments. Although resource allocation design for IRS-assisted multiuser wireless communication systems has been exhaustively investigated in the literature, the optimal design and performance of such systems are still not well understood. To fill this gap, in this paper, we study optimal resource allocation for IRS-assisted multiuser multiple-input single-output (MISO) systems. In particular, we jointly optimize the beamforming at the base station (BS) and the discrete IRS phase shifts to minimize the total transmit power. For attaining the globally optimal solution of the formulated non-convex combinatorial optimization problem, we develop a resource allocation algorithm with guaranteed convergence based on Schur's complement and the generalized Bender's decomposition. Our numerical results reveal that the proposed algorithm can significantly reduce the BS transmit power compared to the state-of-the-art suboptimal alternating optimization-based approach, especially for moderate-to-large numbers of IRS elements.

翻译：智能反射面（IRS）因能够定制无线传播环境，被视作未来通信系统中实现高频谱与高能量效率的低成本方案。尽管现有文献已对IRS辅助多用户无线通信系统的资源分配设计进行了详尽研究，但此类系统的最优设计与性能仍未得到充分理解。为填补这一空白，本文研究了IRS辅助多用户多输入单输出（MISO）系统中的最优资源分配问题。具体而言，我们联合优化基站（BS）的波束赋形与离散IRS相位移位，以最小化总发射功率。为获得所提出的非凸组合优化问题的全局最优解，我们基于舒尔补与广义Benders分解开发了一种具有收敛保证的资源分配算法。数值结果显示，与当前最先进的次优交替优化方法相比，所提算法能显著降低BS发射功率，尤其在IRS元件数量中等至较大时效果更为突出。