Agile and Smart Radio Environments with Intelligent Reflecting Surfaces for Sixth Generation (6G) Communication Systems

众所周知，由于无线信道的随机性，存在着许多不利的影响，如衰落和阴影，这些都限制了任何无线通信系统的性能。然而，自从无线系统出现以来，无线信道一直被认为是网络中一个不可控的实体，到目前为止，这些不利影响已经通过基于收发信机的策略来缓解，例如发送波束形成/预编码、接收分集、自适应调制/编码和使用中继等。这些策略的共同之处在于它们都需要功率来运行，从而导致高能量消耗。即使有这些基于收发器的耗电方案的支持，当前一代的网络也将无法满足我们未来数字社会的性能要求，这意味着新一代网络(如第六代(6G)系统)需要一种范式转换的方法。为了突飞猛进地提高无线网络的性能，同时考虑到无线信道是网络中剩余的主要性能限制实体，我们提出的方法基于使用智能反射表面(IRS)来操纵无线信道。更具体地说，这项研究计划的长期愿景是开发灵活、可重构、可定制和智能的无线电环境，目的是使6G通信系统能够实现超连接，并以经济高效和节能的方式满足未来数字技术的性能要求。由于IRS本质上是无源的，由低成本的反射元件组成，预计拟议的研究计划将产生具有成本效益和能源效率的设计解决方案。IRS是一项开创性的技术，因此，为了实现上述长期愿景，必须解决IRS辅助通信系统的几个新的和复杂的挑战。该研究计划的短期目标包括通过在以下三个方面增加新颖性，以整体方式应对这些挑战：(I)性能限制的特点是在考虑到许多实际约束的情况下，在几个应用领域为IRS辅助通信系统开发分析框架，包括物理层安全和无线功率传输；(Ii)将利用深度学习(DL)来动态配置IRS元素并实时执行信道估计；(Iii)将研究具有成本效益的部署策略，以实现性能收益的最大化。预计拟议的研究计划不仅将产生重大的技术、环境和社会影响，还将有助于HQP在研究和开发下一代通信系统方面的培训。

It is well-known that due to randomness of a wireless channel, there exists many detrimental effects such as fading and shadowing which limit the performance of any wireless communication system. However, since the inception of wireless systems, the wireless channel has been considered an uncontrollable entity of the network, and to date, these detrimental effects have been mitigated through transceiver-based strategies such as transmit beamforming/precoding, receive diversity, adaptive modulation/coding and the use of relays, etc. The commonality among these strategies is that they all require power for their operations and thus contribute to high-energy consumption. Even with the support of these power-hungry transceiver-based schemes, the current generation networks will be unable to meet the performance requirements of our future digital society, which implies that a paradigm-shifting approach is required for new generation networks such as sixth-generation (6G) systems. With an aim to enhance the performance of the wireless networks in leaps and bounds, and keeping in mind that the `wireless channel' is the main performance limiting entity remaining in the network, our proposed methodology is based on manipulation of wireless channels using intelligent reflecting surfaces (IRSs). More specifically, the long-term vision of this research program is to develop agile, reconfigurable, customizable and smart radio environments with a purpose to empower the 6G communication systems with an ability to achieve hyper-connectivity and meet the performance requirements of future digital technologies in a cost-effective and an energy efficient manner. As IRS is fundamentally passive in nature and is comprised of low-cost reflecting elements, it is envisaged that the proposed research program will result in cost-effective and energy-efficient design solutions. IRS is a groundbreaking technology, therefore in order to achieve the aforementioned long term vision, several new and complicated challenges of the IRS-aided communication systems must be addressed. The short-term objectives of this research program include addressing these challenges in a holistic manner by adding novelty in the following three aspects: (i) performance limits will be characterized by developing analytical frameworks for IRS-aided communication systems in several application domains including physical layer security and wireless power transfer taking into account many practical constraints, (ii) Deep Learning (DL) will be leveraged with an aim to dynamically configure IRS elements and perform channel estimation in real-time, and (iii) Cost-effective deployment strategies will be investigated for maximizing performance gains. It is anticipated that the proposed research program will not only generate significant technological, environmental and social impacts but will also contribute to the training of HQPs in research and development of future generation communication systems.