论文标题
通过智能反射表面为多源味o系统分配发电的资源分配
Power-Efficient Resource Allocation for Multiuser MISO Systems via Intelligent Reflecting Surfaces
论文作者
论文摘要
智能反射表面（IRS）由于能力自定义无线传播环境而被认为是下一代无线通信的关键推动者。在本文中，我们研究了IRS辅助多源多输入单输出（MISO）系统的功率效率资源分配。为了最大程度地减少发射功率，在考虑到用户的最低服务质量服务（QoS）的同时，共同优化了接入点（AP）处的波束成形向量和IRS处的相移。为了解决公式优化问题的非跨性别性，开发了内部近似（IA）算法。与无法保证本地最优性的现有设计不同，建议的算法可以融合到Karush-Kuhn-Tucker（KKT）解决方案。我们的仿真结果表明，与基线方案相比，提出的算法的有效性与在能源效率方面利用AP的多个天线相比，部署IRSS更有希望。
Intelligent reflecting surfaces (IRSs) are regarded as key enablers of next-generation wireless communications, due to their capability of customizing the wireless propagation environment. In this paper, we investigate power-efficient resource allocation for IRS-assisted multiuser multiple-input single-output (MISO) systems. To minimize the transmit power, both the beamforming vectors at the access point (AP) and phase shifts at the IRS are jointly optimized while taking into account the minimum required quality-of-service (QoS) of the users. To tackle the non-convexity of the formulated optimization problem, an inner approximation (IA) algorithm is developed. Unlike existing designs, which cannot guarantee local optimality, the proposed algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT) solution. Our simulation results show the effectiveness of the proposed algorithm compared to baseline schemes and reveal that deploying IRSs is more promising than leveraging multiple antennas at the AP in terms of energy efficiency.
