2024/10/22 by Yangyishi Zhang, Khethiwe Mhlope Ziwenjere, Aaron Walker +5 · 1 voice
Engineering · #Advanced MIMO Systems Optimization
paper · doi:10.1109/mnet.2024.3484573
openalex publication_date 2024/10/22 · openalex created_date 2024/10/23 · openalex updated_date 2026/07/22
The 5G wireless network is now part of the critical national infrastructure of developed nations. Wireless network operators must strive to improve performance in order to be competitive, whilst reducing costs in order to be profitable. State-of-the-art technology informs the future direction of the industry but network operators’ operational and commercial needs also need to inform the direction of research. This industrial review sheds light on an ongoing technological convergence from the viewpoint of wireless network operators that hold direct responsibility in deploying new networking technologies. An evolving paradigm called the “Smart Wireless Environment” (SWE) brings together disparate research topics in revolutionising physical layer networking. A critical role of SWE is to overcome, or significantly mitigate, the service degradation due to fading wireless channels. Therefore, we focus our attention to a pragmatic, narrow-sense application of SWE, which we term as network stabilization. Besides classic end-to-end (E2E) fading countermeasures, network operators could also adopt SWE to augment the propagation background in complex real-life environments. Akin to the synthesis of a filter with flat response, stabilized artificial fading channels can be engineered from augmented scattering clusters (ASCs). The ability to tailor the fading channel response could offer a network operator useful competitive advantage. However, the SWE paradigm is still at a low technology readiness level (TRL). The challenge is for operators to work out how to cost-effectively implement SWE to deliver real user benefit, building on the present-day installed network. To this end, we provide a technical analysis of the synergy between SWE enablers: holographic metasurfaces to augment the environment, wireless sensing to monitor the environment, and machine intelligence to control the environment. The expected performance advantages of SWE are numerically investigated. Finally, major roadblocks in SWE commercialization are also identified.