智能反射面辅助无线通感系统的性能优化研究

    智能反射面（RIS）能够改变其每个单元的电磁特性，从而重新配置发射端和接收端之间的信号。RIS辅助的无线系统中，可以通过设计其被动波束赋形，达到优化系统性能的目的。本文以RIS辅助的无线通信和无线感知系统为背景，分别研究了系统性能的优化方案。

    在RIS辅助多用户多输入单输出系统的下行链路中，研究了如何提高无线通信系统性能、提供决策的灵活性。用户总速率和发射功率是此类系统中的两个重要性能指标。然而，大多数现有工作只优化了其中一个，导致另一个性能可能严重下降。受此启发，在本文中，制定了一个多目标优化问题，旨在同时最大化用户总速率并最小化发射功率。根据早期关于总速率最大化问题适应度地形的分析工作，所提出的问题应具有多峰特性。考虑到RIS的硬件限制，其每个单元的相位值均设置为离散。为了解决这个多峰的非凸优化问题，提出了一种新颖的多目标进化联合波束赋形框架，以在两个相互冲突的目标之间找到不同的权衡解。具体来说，采用不同的多目标进化算法和多峰多目标进化算法来优化RIS的被动波束赋形，而对应的基站主动波束赋形则通过经典的迫零算法获得。仿真结果验证了基于支配关系的进化算法在处理联合波束赋形问题中的有效性。

    在无源RIS辅助的毫米波雷达非视距检测系统中，研究了无线感知场景下，无源RIS如何提高雷达检测性能，使得雷达提前感知到物体并减少碰撞概率。考虑一个实际户外场景，道路交叉处被遮挡形成盲角。不确定其交叉角和坡度的情况下，检测目标方向、无源RIS的部署方向也都有可能变化。现有工作目前还没有针对角度变化的实时性和鲁棒性的考虑。受此启发，提出了一个最大化最小的接收功率的优化问题。为了减少雷达与RIS间的同步开销，提出利用无源RIS覆盖一定角度范围内的区域。为解决无源RIS高维变量导致的多峰问题，提出了一个新颖的基于相似度距离的小生境遗传算法。具体来说，该算法将种群划分为不同小生境内的物种，物种内外交换信息，多个局部最优最终促进收敛至全局最优。针对变量的高维特性，提出了三种不同的变量算子，探讨降低变量维度的影响。通过比较不同算法、不同反射物和不同角度下雷达接收功率的区别，证实了无源RIS应用于雷达非视距检测的有效性和鲁棒性。

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