论文标题
最小符号 - 误差概率符号级的预编码和智能反射表面
Minimum Symbol-Error Probability Symbol-Level Precoding with Intelligent Reflecting Surface
论文作者
论文摘要
最近，使用智能反射表面（IRS）在无线通信中引起了极大的关注。通过智能调整被动反射角，IRS能够协助基站（BS）扩展覆盖范围并提高光谱效率。本文考虑了一个反映设计的联合符号级预编码（SLP）和IRS，以最大程度地减少IRS辅助的Multiuser Miso Downink中预期用户的符号误差概率（SEP）。我们制定了SEP最小化问题，为所有QAM和PSK星座的所有用户都统一地表现出色。由此产生的问题是非凸，我们求助于交替最小化以获得固定解决方案。仿真结果表明，在IRS的帮助下，我们提出的设计确实提高了位率的性能。特别是，当IRS元素数量较大时，性能提高很大。
Recently, the use of intelligent reflecting surface (IRS) has gained considerable attention in wireless communications. By intelligently adjusting the passive reflection angle, IRS is able to assist the base station (BS) to extend the coverage and improve spectral efficiency. This paper considers a joint symbol-level precoding (SLP) and IRS reflecting design to minimize the symbol-error probability (SEP) of the intended users in an IRS-aided multiuser MISO downlink. We formulate the SEP minimization problems to pursue uniformly good performance for all users for both QAM and PSK constellations. The resulting problem is non-convex and we resort to alternating minimization to obtain a stationary solution. Simulation results demonstrate that under the aid of IRS our proposed design indeed enhances the bit-error rate performance. In particular, the performance improvement is significant when the number of IRS elements is large.
