Abstract
Beyond-diagonal reconfigurable intelligent surface (BD-RIS) has recently been introduced to enable advanced control over electromagnetic waves to further increase the benefits of traditional RIS in enhancing signal quality and improving spectral and energy efficiency for next-generation wireless networks. A significant issue in designing and deploying BD-RIS is the tradeoff between its performance and circuit complexity. Despite some efforts in exploring optimal architectures with the lowest circuit complexities for ideal BD-RIS, architecture discovery for non-ideal BD-RIS remains uninvestigated. Therefore, how non-idealities and circuit complexity jointly affect the performance of BD-RIS remains unclear, making it difficult to achieve the performance - circuit complexity tradeoff in the presence of non-idealities. Essentially, architecture discovery for non-ideal BD-RIS faces challenges from both the computational complexity of global architecture search and the difficulty in achieving global optima. To tackle these challenges, we propose a learning-based two-tier architecture discovery framework (LTTADF) consisting of an architecture generator and a performance optimizer to jointly discover optimal architectures of non-ideal BD-RIS given specific circuit complexities, which can effectively explore over a large architecture space while avoiding getting trapped in poor local optima and thus achieving near-optimal solutions for the performance optimization. Numerical results provide valuable insights for deploying non-ideal BD-RIS considering the performance - circuit complexity tradeoff.
Abstract (translated)
超越对角线可重构智能表面（BD-RIS）最近被引入，以实现对电磁波的高级控制，从而进一步提升传统RIS在增强信号质量和提高频谱及能源效率方面的能力，为下一代无线网络提供更多的优势。设计和部署BD-RIS时面临的一个重要问题在于其性能与电路复杂度之间的权衡。尽管有一些研究致力于探索理想BD-RIS的最低电路复杂度架构，但对于非理想的BD-RIS架构发现的研究仍然未被开展。因此，在非理想条件下，BD-RIS性能如何受到非理想性和电路复杂度共同影响尚不清楚，这使得在存在非理想性的情况下实现性能与电路复杂度之间的权衡变得困难。 实际上，对于非理想的BD-RIS来说，架构发现面临着来自全局架构搜索计算复杂性的挑战以及达到全局最优解的难度。为了解决这些问题，我们提出了一种基于学习的双层架构发现框架（LTTADF），该框架由一个架构生成器和一个性能优化器组成，它们可以共同在给定特定电路复杂度的情况下，探索非理想BD-RIS的最佳架构，从而有效地避免陷入次优解并实现接近最优的解决方案。数值结果为考虑性能与电路复杂度权衡的非理想BD-RIS部署提供了有价值的见解。 此框架的目标是通过自动化和优化的方法来解决设计非理想BD-RIS时遇到的问题，使研究者能够更高效地探索不同架构的可能性，并找到在特定条件下的最佳平衡点。这将有助于推动无线通信技术的发展，并为未来的无线网络带来更大的灵活性和效率。
URL
https://arxiv.org/abs/2510.15701
