Radio Frequency Integrated Circuit Design

Neueste Paper

• Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies

  Baktash Behmanesh, Ahmad Rezvanitabar · 30. April 2026

  This paper provides a concise yet comprehensive review of recent advancements in millimeter-wave (mm-wave) oscillators below 100 GHz and sub-terahertz (sub-THz/THz) oscillators above 100 GHz for next-generation computing and communication systems, including 5G, 6G, and beyond. Various design approac…

• Alpha-RF: Automated RF-Filter-Circuit Design with Neural Simulator and Reinforcement Learning

  Nhat Tran, Chenjie Hao, Alexander Stameroff, Anh-Vu Pham, Yubei Chen · 3. März 2026

  Accurate, high-performance radio-frequency (RF) filter circuits are ubiquitous in radio-frequency communication and sensing systems for accepting and rejecting signals at desired frequencies. Conventional RF filter design process involves manual calculations of design parameters, followed by intuiti…

• Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices

  Muhammad Kamran Saeed, Ashfaq Khokhar, Shakil Ahmed · 1. Januar 2026

  Next-generation wireless technologies such as 6G aim to meet demanding requirements such as ultra-high data rates, low latency, and enhanced connectivity. Extremely Large-Scale MIMO (XL-MIMO) and Reconfigurable Intelligent Surface (RIS) are key enablers, with XL-MIMO boosting spectral and energy eff…

• MOTIF-RF: Multi-template On-chip Transformer Synthesis Incorporating Frequency-domain Self-transfer Learning for RFIC Design Automation

  Houbo He, Yizhou Xu, Lei Xia, Yaolong Hu, Fan Cai, Taiyun Chi · 1. Dezember 2025

  This paper presents a systematic study on developing multi-template machine learning (ML) surrogate models and applying them to the inverse design of transformers (XFMRs) in radio-frequency integrated circuits (RFICs). Our study starts with benchmarking four widely used ML architectures, including M…

• PEARL: Peer-Enhanced Adaptive Radio via On-Device LLM

  Ju-Hyung Lee, Yanqing Lu, Klaus Doppler · 29. Oktober 2025

  We present PEARL (Peer-Enhanced Adaptive Radio via On-Device LLM), a framework for cooperative cross-layer optimization in device-to-device (D2D) communication. Building on our previous work on single-device on-device LLMs, PEARL extends the paradigm by leveraging both publisher and subscriber state…