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，存在许多不利的影响，如衰落和阴影，这限制了任何无线通信系统的性能。然而，自从无线系统开始以来，无线信道一直被认为是网络的不可控实体，并且迄今为止，这些有害影响已经通过基于收发器的策略（诸如发送波束成形/预编码、接收分集、自适应调制/编码和中继的使用）来减轻。这些策略的共同之处在于，它们都需要电力来进行操作，从而导致高能耗。即使有这些高功耗的基于以太网的方案的支持，当前一代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（6 G）系统）需要范式转换方法。为了提高性能的无线网络的跨越式发展，并记住，“无线信道”是主要的性能限制实体留在网络中，我们提出的方法是基于操纵的无线信道使用智能反射面（IRS）。更具体地说，该研究计划的长期愿景是开发灵活，可重新配置，可定制和智能的无线电环境，旨在使6 G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本质上是被动的，并且由低成本的反射元件组成，因此可以设想，拟议的研究计划将产生具有成本效益和节能的设计解决方案。IRS是一项突破性的技术，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奇来全面应对这些挑战：（i）性能限制将通过在包括物理层安全和无线功率传输的若干应用领域中开发用于IRS辅助通信系统的分析框架来表征，同时考虑到许多实际约束，（ii）深度学习（DL）将被用于动态配置IRS元素并实时执行信道估计，以及（iii）将研究具有成本效益的部署策略以最大限度地提高性能。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，而且还将有助于培训HQP研究和开发下一代通信系统。

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.