Working Time: 9:30-18:00
2026 The 11th International Conference on Integrated Circuits and Microsystems
    Email: icicm_conf@vip.163.com
    Secretary: Ms. Carrie Lim (林老师)

Track 24: High-Performance RF Transceiver Front-End ICs for Next-Generation Wireless Communications

Track 24: 面向下一代无线通信的高性能射频收发机前端芯片

Organizers / 组织者

Organizer / 组织者
Youming Zhang 张有明
Associate Researcher, Southeast University
东南大学,副研究员

Abstract / 论坛简介

English: RF transceiver front-end ICs—including core modules such as low-noise amplifiers (LNA), power amplifiers (PA), mixers, and programmable gain amplifiers (PGA)—serve as the critical gateway of wireless communication systems. As 5G-Advanced/6G communications evolve toward higher frequency bands (FR3, millimeter-wave, terahertz), and with the emergence of new application scenarios such as satellite internet and phased-array radar, RF front-ends face systemic challenges in bandwidth, linearity, efficiency, power consumption, and chip area. In recent years, Doherty PA architectures have achieved continuous breakthroughs in power back-off efficiency; Mixer-First and N-Path architectures have provided new approaches for wideband receivers; AI/ML methods have begun to deeply engage in RF circuit topology discovery and parameter optimization; and the integration level of front-end modules in the millimeter-wave band has been continuously improving. This forum aims to exchange technological frontiers in RF integrated circuit design and explore development trends.

中文: 射频收发机前端芯片——包括低噪声放大器(LNA)、功率放大器(PA)、混频器(Mixer)、可编程增益放大器(PGA)等核心模块——是无线通信系统的"咽喉"所在。随着5G-A/6G通信向更高频段(FR3、毫米波、太赫兹)演进,以及卫星互联网、相控阵雷达等新应用场景的涌现,射频前端在带宽、线性度、效率、功耗和面积等方面面临系统性挑战。近年来,Doherty PA架构在功率回退效率方面持续突破;Mixer-First与N-Path架构为宽带接收机提供了新思路;AI/ML方法开始深度介入射频电路拓扑发现与参数优化;毫米波频段的前端模块集成度不断提升。本论坛旨在交流射频集成电路设计领域的技术前沿,探讨发展趋势。

Topics / 讨论主题

低噪声放大器与接收机前端
LNA & Receiver Front-Ends
功率放大器与发射机
Power Amplifiers & Transmitters
通感一体化收发机
ISAC/JCAS Transceivers
毫米波与太赫兹前端
mm-Wave & THz Front-Ends
可编程增益放大器与可变增益放大器
PGA & VGA
全双工收发机与自干扰消除
Full-Duplex Transceivers & Self-Interference Cancellation
AI辅助射频电路设计:机器学习驱动的电路拓扑发现、参数优化与智能校准
AI-Assisted RF Design: ML-driven circuit topology discovery, parameter optimization & intelligent calibration