Towards Sustainable ICT: Sparse Ubiquitous Networks based on Reconfigurable Intelligent Surfaces

从环境的角度来看，对高数据速率、低延迟和高可靠性的泛在无线通信服务的不断增长的需求被认为是不可持续的。特别是，新兴的毫米波(mm-Wave)范围内的高速率服务需要大量的基站来覆盖更大的区域或城市环境，这导致了能源和资源消耗的显著增加。其主要思想是智能地将其他未使用和浪费的信号反射回给用户的路径上，以提高整体覆盖和吞吐量。然而，这种RISS通常需要大量主动可调组件来动态地将反射重定向到用户。相关的能源消耗阻止了以这种方式确保可持续性。该项目建立在通过智能可重构表面增强无线链路的想法基础上，但它增加了一个重要的关键因素，以实际实现可持续发展，同时提供无线服务覆盖所需的改进：稀疏性。在这些可重构表面上稀疏放置可调元件，然后称为稀疏可重构智能表面(SRIS)，可显著提高能效。此外，在部署这些SRIS时也使用稀疏性，通过最小化制造成本和使用的资源以及总体能源消耗，进一步提高可持续性。这些项目的关键组件包括开发基于物理的SRIS模型，基于结合元表面设计和稀疏化思想的整体设计方法，通过提高效率的电磁模拟技术进行通道建模，以及优化资源分配和部署(通过现代凸优化和松弛以及基于人工智能(AI)的方法)以最大化SRIS改进。原型和测量将验证工作概念。该项目将为未来的高性能无线网络铺平道路，这些网络在设计上是节能和可持续的。

The ever-increasing demand for ubiquitous wireless communication services with high data rate, low latency, and high reliability is considered unsustainable from an environmental perspective. In particular, the emerging high-rate services in the millimetre-wave (mmWave) range require a large number of base stations to cover larger areas or urban environments, which leads to a significant increase in the consumption of energy and resources.Several ideas exist to improve these networks without the need for additional base stations; in particular, reconfigurable intelligent surfaces (RIS) have recently been proposed as sustainable alternatives for many application scenarios. The main idea is to intelligently reflect otherwise unused and wasted signals back onto a path to the user, to improve overall coverage and throughput. However, such RISs typically require a large number of actively tunable components to dynamically redirect the reflections towards the users. The associated energy consumption prevents sustainability from being ensured in this way.This project builds on the idea of enhancing the wireless links via smart reconfigurable surfaces, but it adds an important key ingredient to actually achieve sustainability, while providing the needed improvement for wireless service coverage: sparsity. Sparse placement of tunable components on these reconfigurable surfaces, then referred to as sparse reconfigurable intelligent surfaces (SRISs), results in significant energy efficiency improvement. Beyond that, employing sparsity also in the deployment of these SRISs, further improves sustainability, by minimizing both manufacturing costs and used resources as well as overall energy consumption.Key components of the projects include the development of physics-based models of SRIS and a holistic design methodology based on combining ideas from metasurface design and sparsification, channel modelling via efficiency-enhancing electromagnetic simulation techniques, and optimisation of resource allocation and deployment (via modern convex optimisation and relaxation as well as artificial intelligence (AI)-based methods) to maximize SRIS improvement. Prototypes and measurements will prove the working concepts.This project will pave the way toward future high-performance wireless networks that are energy-efficient and sustainable by design.