  Large Language Models (LLMs) have immense potential to transform the
telecommunications industry. They could help professionals understand complex
standards, generate code, and accelerate development. However, traditional LLMs
struggle with the precision and source verification essential for telecom work.
To address this, specialized LLM-based solutions tailored to telecommunication
standards are needed. Retrieval-augmented generation (RAG) offers a way to
create precise, fact-based answers. This paper proposes TelecomRAG, a framework
for a Telecommunication Standards Assistant that provides accurate, detailed,
and verifiable responses. Our implementation, using a knowledge base built from
3GPP Release 16 and Release 18 specification documents, demonstrates how this
assistant surpasses generic LLMs, offering superior accuracy, technical depth,
and verifiability, and thus significant value to the telecommunications field.
