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首页> 外文期刊>Wireless Communications Letters, IEEE >The Low-Complexity Design and Optimal Training Overhead for IRS-Assisted MISO Systems
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The Low-Complexity Design and Optimal Training Overhead for IRS-Assisted MISO Systems

机译：针对IRS辅助MISO系统的低复杂性设计和最佳训练开销

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摘要

A low-complexity channel estimation and passive beamforming design for intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) systems is proposed. Specifically, we present the low-complexity framework for maximizing the achievable rate of IRS-assisted MISO systems with discrete phase shifters at each IRS element. In contrast to existing solutions, the training set of IRS reflection coefficient matrix is pre-designed and the effective superposition channel estimation and transmit beamforming design are then performed for each IRS reflection coefficient matrix in the training set. Following this, the IRS reflection optimization is simplified by selecting the one that maximizes the achievable rate from the pre-designed training set. Secondly, we analyze the theoretical performance of the proposed framework and provide the optimal training overhead for maximizing the effective achievable rate given the channel coherence time. Finally, numerical simulations evaluate the rate performance of the proposed design. In particular, simulation results demonstrate that the proposed framework is a competitive option in practical communication systems with channel estimation errors.
机译：提出了用于智能反射表面（IRS）的低复杂性信道估计和被动波束形成设计 - 拟议的多输入单输出（MISO）系统。具体地，我们介绍了低复杂性框架，用于最大化每个IRS元件的离散相移器的IRS辅助MISO系统的可实现速率。与现有解决方案相反，预先设计IRS反射系数矩阵的训练集，然后对训练集中的每个IRS反射系数矩阵执行有效的叠加信道估计和传输波束形成设计。在此之后，通过选择从预先设计的训练集中最大化可实现的速率的IRS反射优化。其次，我们分析了所提出的框架的理论性能，并为鉴于通道连贯时间的有效可实现的速率提供最佳训练开销。最后，数值模拟评估了所提出的设计的速率性能。特别地，仿真结果表明，所提出的框架是具有信道估计误差的实际通信系统中的竞争选择。

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