{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://froggit.ai/public/capsules/e7c9b386-fbf6-44d8-af54-c211f90c3340","identifier":"e7c9b386-fbf6-44d8-af54-c211f90c3340","url":"https://froggit.ai/public/capsules/e7c9b386-fbf6-44d8-af54-c211f90c3340","name":"Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies","text":"# Recent Advances in mm-Wave and Sub-THz/THz Oscillators for FutureG Technologies\n\nSource-backed public reference for arXiv:2604.26903.\n\n**Authors:** Baktash Behmanesh, Ahmad Rezvanitabar\n**Primary source:** https://arxiv.org/abs/2604.26903\n**Published:** 2026-04-29T17:12:18Z\n**Updated:** 2026-04-29T17:12:18Z\n**Categories:** eess.SP, cs.AI, cs.AR, cs.ET, eess.SY\n\n## Abstract Summary\nThis 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 approaches, including CMOS, SiGe, and III-V semiconductor technologies, are explored in terms of performance metrics such as phase noise, output power, efficiency, frequency tunability, and stability. The review highlights key challenges in achieving high-performance and reliable oscillator designs while discussing emerging techniques for performance enhancement. By evaluating recent design trends, this work aims to offer valuable insights and design guidelines that facilitate the development of robust mm-wave and sub-THz/THz oscillators for future communication, computing, and sensing applications.\n\n## Public Use Notes\n- arXiv metadata/abstract summary only; not independent replication or endorsement.\n- Use as a cited research reference for discovery, retrieval, and agent context.\n- For clinical, security, operational, or deployment-sensitive topics, treat as research context, not medical, legal, safety, or engineering advice.\n\n## Source\n- https://arxiv.org/abs/2604.26903\n","keywords":["eess.SP","cs.AI","cs.AR","cs.ET","eess.SY"],"about":[],"citation":["https://arxiv.org/abs/2604.26903"],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://froggit.ai"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://froggit.ai"},"dateCreated":"2026-04-30T06:00:04.734000Z","dateModified":"2026-06-19T14:20:13Z","isBasedOn":"https://arxiv.org/abs/2604.26903","additionalProperty":[{"@type":"PropertyValue","name":"trust_level","value":40},{"@type":"PropertyValue","name":"verification_status","value":"sources_verified"},{"@type":"PropertyValue","name":"provenance_status","value":"valid"},{"@type":"PropertyValue","name":"evidence_level","value":"primary_source"},{"@type":"PropertyValue","name":"content_hash","value":"0856278a0987392169c9bf740fdaaadee1d4112a2c42e9945736394219860c76"}]}