Intelligent reflecting surface (IRS) serves as an emerging paradigm to enhance the wireless transmission with a low hardware cost and a reduced power consumption. In this letter, we investigate the IRS-assisted downlink multi-input multi-output (MIMO) system, where an Alice-Bob pair wishes to communicate with the assist of IRS. Our goal is to maximize the spectral efficiency by designing the active beamformer at Alice and the passive reflecting phase shifters (PSs) at the IRS, which turns out to be an intractable mixed integer non-convex optimization problem. To tackle this problem, we propose an efficient algorithm to obtain an effective solution. Specifically, the PSs at the IRS are optimized to maximize the sum of gains of different paths. Such a criterion is also referred to as the maximizing the sum of gains (MSG) principle. Then, an alternating direction method of multipliers (ADMM) algorithm is developed to solve the MSG-based optimization problem. With the obtained PSs, the beamformer at Alice is obtained by classic singular value decomposition (SVD) and water-filling (WF) solutions.
翻译:智能反射表面(IRS)是一个新兴的范例,用低硬件成本和减少电耗来增强无线传输。我们在信中调查了IRS协助的下链多投入多产出产出(MIMO)系统,爱丽丝-鲍博一对希望在IRS的协助下进行交流。我们的目标是通过设计爱丽丝的活光束和IRS的被动反射相转换器(PS),最大限度地提高光谱效率,因为后者发现是一个棘手的混合整数非凝聚优化问题。为了解决这一问题,我们提出了一种高效的算法,以获得有效的解决方案。具体地说,IRS的 PS得到优化,以最大限度地实现不同路径收益的总和。这种标准也被称为最大限度地实现收益总和(MSG)原则。然后,开发了一种交替方向的乘数算法,以解决基于MSG的优化问题。在获得的 PSS后,Alice的光谱通过典型的单值解位和填水解决方案获得。