# RIS-Enabled Smart Wireless Environments: Fundamentals and Distributed Optimization arXiv: https://arxiv.org/abs/2512.18788 ยท HTML: https://mlsanity.com/paper/2512.18788/ ## Key facts - No citing papers in the map yet (data through 14 Oct 2026). - Builds on 64 of its 108 references that are in the map. - First posted on arXiv 21 Dec 2025. ## Builds on (most cited first, 30 of 64) - [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017) - [Neural Machine Translation by Jointly Learning to Align and Translate](https://mlsanity.com/paper/1409.0473/) (2014) - [Asynchronous Methods for Deep Reinforcement Learning](https://mlsanity.com/paper/1602.01783/) (2016) - [Evolution Strategies as a Scalable Alternative to Reinforcement Learning](https://mlsanity.com/paper/1703.03864/) (2017) - [Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming](https://mlsanity.com/paper/1810.03961/) (2018) - [Reconfigurable Intelligent Surfaces: Principles and Opportunities](https://mlsanity.com/paper/2007.03435/) (2020) - [Attention Mechanism in Neural Networks: Where it Comes and Where it Goes](https://mlsanity.com/paper/2204.13154/) (2022) - [Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial](https://mlsanity.com/paper/2007.02759/) (2020) - [PyGAD: An Intuitive Genetic Algorithm Python Library](https://mlsanity.com/paper/2106.06158/) (2021) - [Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization](https://mlsanity.com/paper/1907.06002/) (2019) - [Dynamic Metasurface Antennas for 6G Extreme Massive MIMO Communications](https://mlsanity.com/paper/2006.07838/) (2020) - [Indoor Signal Focusing with Deep Learning Designed Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/1905.07726/) (2019) - [Pervasive Machine Learning for Smart Radio Environments Enabled by Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2205.03793/) (2022) - [Over-the-Air Computation for 6G: Foundations, Technologies, and Applications](https://mlsanity.com/paper/2210.10524/) (2022) - [Stacked Intelligent Metasurfaces for Efficient Holographic MIMO Communications in 6G](https://mlsanity.com/paper/2305.08079/) (2023) - [Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design](https://mlsanity.com/paper/2101.09137/) (2021) - [Phase Configuration Learning in Wireless Networks with Multiple Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/2010.04376/) (2020) - [Decomposition by Partial Linearization: Parallel Optimization of Multi-Agent Systems](https://mlsanity.com/paper/1302.0756/) (2013) - [RISs and Sidelink Communications in Smart Cities: The Key to Seamless Localization and Sensing](https://mlsanity.com/paper/2301.03535/) (2023) - [Over-the-Air Edge Inference via End-to-End Metasurfaces-Integrated Artificial Neural Networks](https://mlsanity.com/paper/2504.00233/) (2025) - [Hybrid Reconfigurable Intelligent Metasurfaces: Enabling Simultaneous Tunable Reflections and Sensing for 6G Wireless Communications](https://mlsanity.com/paper/2104.04690/) (2021) - [On the Tacit Linearity Assumption in Common Cascaded Models of RIS-Parametrized Wireless Channels](https://mlsanity.com/paper/2302.04993/) (2023) - [A Hardware Architecture for Reconfigurable Intelligent Surfaces with Minimal Active Elements for Explicit Channel Estimation](https://mlsanity.com/paper/2002.10371/) (2020) - [Reconfigurable, Intelligent, and SustainableWireless Environments for 6G Smart Connectivity](https://mlsanity.com/paper/2110.07547/) (2021) - [Leveraging RIS-Enabled Smart Signal Propagation for Solving Infeasible Localization Problems](https://mlsanity.com/paper/2204.11538/) (2022) - [Reconfigurable Intelligent Surfaces for 6G: Emerging Hardware Architectures, Applications, and Open Challenges](https://mlsanity.com/paper/2312.16874/) (2023) - [Channel Estimation with Reconfigurable Intelligent Surfaces -- A General Framework](https://mlsanity.com/paper/2110.00553/) (2021) - [Beyond Diagonal Reconfigurable Intelligent Surfaces: From Transmitting and Reflecting Modes to Single-, Group-, and Fully-Connected Architectures](https://mlsanity.com/paper/2205.02866/) (2022) - [Metasurfaces-Enabled Wave Computing for Future Wireless Systems: Opportunities and Challenges](https://mlsanity.com/paper/2501.05173/) (2025) - [Over-the-Air Semantic Alignment with Stacked Intelligent Metasurfaces](https://mlsanity.com/paper/2512.05657/) (2025) ## Abstract (arXiv) This chapter overviews the concept of Smart Wireless Environments (SWEs) motivated by the emerging technology of Reconfigurable Intelligent Surfaces (RISs). The operating principles and state-of-the-art hardware architectures of programmable metasurfaces are first introduced. Subsequently, key performance objectives and use cases of RIS-enabled SWEs, including spectral and energy efficiency, physical-layer security, integrated sensing and communications, as well as the emerging paradigm of over-the-air computing, are discussed. Focusing on the recent trend of Beyond-Diagonal (BD) RISs, two distributed designs of respective SWEs are presented. The first deals with a multi-user Multiple-Input Single-Output (MISO) system operating within the area of influence of a SWE comprising multiple BD-RISs. A hybrid distributed and fusion machine learning framework based on multi-branch attention-based convolutional Neural Networks (NNs), NN parameter sharing, and neuroevolutionary training is presented, which enables online mapping of channel realizations to the BD-RIS configurations as well as the multi-user transmit precoder. Performance evaluation results showcase that the distributedly optimized RIS-enabled SWE achieves near-optimal sum-rate performance with low online computational complexity. The second design focuses on the wideband interference MISO broadcast channel, where each base station exclusively controls one BD-RIS to serve its assigned group of users. A cooperative optimization framework that jointly designs the base station transmit precoders as well as the tunable capacitances and switch matrices of all metasurfaces is presented. Numerical results demonstrating the superior sum-rate performance of the designed RIS-enabled SWE for multi-cell MISO networks over benchmark schemes, considering non-cooperative configuration and conventional diagonal metasurfaces, are presented.