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

点击翻译按钮获取中文摘要

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.