Autonomous Discovery of Wireless Communications Algorithms

2026-07-20

AI Summary

This work addresses the longstanding trade-off between performance and complexity in physical-layer algorithm design for wireless communications. The authors propose AITE, a novel framework that, for the first time, leverages large language model (LLM)-driven evolutionary search to autonomously discover communication algorithms. Using this approach, they successfully devise new algorithms for OTFS equalization and pilotless OFDM reception. The generated algorithms exhibit both high interpretability and superior performance: in OTFS equalization, they outperform the current state-of-the-art while reducing latency by 3.6×; in pilotless OFDM reception, they yield the first explicit analytical solution that matches the performance of neural receivers.

Abstract

Large language model (LLM)-driven evolutionary search is an emerging algorithm-discovery paradigm that has already produced novel results in several scientific fields. Yet its application to wireless communications remains largely unexplored. To bridge this gap, we introduce The AI Telco Engineer (AITE), a framework to autonomously design algorithms for complex communication problems, while navigating performance-complexity tradeoffs. We showcase AITE on two challenging physical-layer problems: designing an equalizer for an orthogonal time-frequency space (OTFS) system, and constructing a receiver algorithm for an orthogonal frequency-division multiplexing (OFDM) system using a custom constellation and operating without pilots. For the first task, AITE develops algorithms that outperform the best-known solutions while reducing computational latency by a factor of 3.6 compared to the strongest baseline. For the second task, it discovers the first explicit, explainable algorithms that achieve performance parity with state-of-the-art neural receivers. These results demonstrate the strong potential of LLM-driven evolutionary search for the autonomous discovery of next-generation wireless communications algorithms.

Problem

• wireless communications
• algorithm discovery
• LLM-driven evolutionary search
• physical-layer algorithms
• performance-complexity tradeoff

Innovation

• LLM-driven evolutionary search
• autonomous algorithm discovery
• wireless communications
• OTFS equalization
• explainable receiver design