Year: 2019
Type: preprint
Abstract: The concept of CogRF, a novel tunable radio frequency (RF) frontend that uses artificial intelligence (AI) to meet mission requirements for beyond 5G and 6G systems, is introduced. CogRF utilizes AI as the core to control and operate RF system components with the objective of optimizing the overall system performance. An overview of the vital elements that make up CogRF as well as the overall hierarchy of the envisioned CogRF system is provided, and potential RF components and control parameters are discussed. AI-powered flexible RF front ends, provide new opportunities to identify to enhance security, speed up optimization of device configurations, further refine radio design, improve existing spectrum sharing operations, and develop device health analytics. Top research challenges for CogRF systems have also been described and potential research directions are provided.
Source: arXiv (Cornell University)
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: SpecEES: Collaborative Research: Enabling Spectrum and Energy-Efficient Dynamic Spectrum Access Wireless Networks using Neuromorphic Computing, Collaborative Research: Delay-Sensitive Hybrid Broadcast/Unicast Traffic over Heterogeneous Cellular Networks, NeTS: Medium: Implications of Receiver RF Front End Nonlinearity on Network Performance: Fundamentals, Limitations, and Management Strategies, NeTS: Small: Spatial Spectrum Sensing-Based Device-to-Device (D2D) Networks, EARS: Toward Harmonious Coexistence of Heterogeneous Wireless Services
OpenAlex ID: W2972489709