AI-augmented intelligent RFICs for transmitter predistortion for 5G and 6G wireless and space communication applications

用于 5G 和 6G 无线和空间通信应用的发射机预失真的 AI 增强型智能 RFIC

• 批准号: 571671-2021
• 负责人: Helaoui, Mohamed
• 金额: $ 3.64万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=729189
• 关键词: AI; augmented; intelligent; RFICs; transmitter

Signal bandwidths have been increasing five times in every generation from 2G, reaching 100 MHz in 5G. Digital Predistortion (DPD) techniques were introduced in 3G and have been used since to reduce the impairments in RF front-ends, allowing the use of more energy efficient components and modes of operation at the cost of additional computation in baseband. As a result, the energy consumption of 3G base stations were reduced by up to 10%.In current DPD technology, the signal processing and transmitter components operate at few times the signal bandwidth to carry the correction information along with the signal information to the RF front-end. With wider signal bandwidths, 5G DPD processing complexity and energy consumption have increased to a point that offsets the energy efficiency gains in the RF frontend. Moreover, a full receiver is needed to monitor the RF front-end and adapt to its behavioural changes. This baseband-RF-baseband loop is complex, expensive, and slow in following the system changes. With the use of beamforming techniques, 5G+ Front-ends operating conditions vary rapidly and current DPD technology is unable to track these fast changes.This project aims to design an artificial intelligence (AI)-augmented RFIC predistorted front-end with the ability to quickly adapt to changes in the RF front-end environment and operating conditions. By including sensors to monitor the RF front-end environmental and operating conditions changes, and an AI engine to adapt the predistorter to these changes, the proposed solution will reduce the signal processing complexity, energy consumption, and latency. This solution would be the first truly intelligent RF system that is aware of its environment and able to adapt to changes. A proof-of-concept RFIC will be designed using state-of-the-art Gallium Nitride (GaN) nano technology and fabricated in world-leading nanofab facilities.

从2G开始，信号带宽每一代都增加了五倍，在5G中达到100 MHz。数字预失真（DPD）技术在3G中引入，并且从那时起一直用于减少RF前端中的损伤，从而允许以基带中的额外计算为代价使用更节能的组件和操作模式。在当前的DPD技术中，信号处理和发射机组件工作在几倍于信号带宽的带宽上，以便将校正信息沿着信号信息一起传送到RF前端。随着更宽的信号带宽，5G DPD处理复杂性和能耗已经增加到抵消RF前端能效增益的程度。此外，需要一个完整的接收器来监控RF前端并适应其行为变化。这种基带-RF-基带环路复杂、昂贵，并且跟踪系统变化的速度慢。随着波束成形技术的使用，5G+前端的工作条件变化很快，目前的DPD技术无法跟踪这些快速变化。本项目旨在设计一种人工智能（AI）增强的RFIC预失真前端，能够快速适应RF前端环境和工作条件的变化。通过包括传感器来监控RF前端环境和操作条件的变化，以及AI引擎来调整预失真器以适应这些变化，所提出的解决方案将降低信号处理的复杂性，能耗和延迟。该解决方案将是第一个真正的智能射频系统，能够感知其环境并适应变化。RFIC概念验证将使用最先进的氮化镓（GaN）纳米技术设计，并在世界领先的纳米工厂中制造。