Agentic Semantic Control for Autonomous Wireless Space Networks: Extending Space-O-RAN with MCP-Driven Distributed Intelligence

TL;DR

This paper introduces a semantic agentic layer for lunar wireless networks, enhancing autonomy and adaptability through distributed cognitive agents and MCP-driven communication, addressing the unique challenges of lunar surface operations.

Contribution

It extends Space-O-RAN with a semantic layer using MCP and A2A protocols, enabling context-aware, distributed decision making for lunar wireless networks.

Findings

Enhanced autonomy and robustness in lunar wireless communication systems.

Implementation of delay-adaptive reasoning and semantic compression strategies.

Distributed agents effectively coordinate across lunar surface infrastructure.

Abstract

Lunar surface operations impose stringent requirements on wireless communication systems, including autonomy, robustness to disruption, and the ability to adapt to environmental and mission-driven context. While Space-O-RAN provides a distributed orchestration model aligned with 3GPP standards, its decision logic is limited to static policies and lacks semantic integration. We propose a novel extension incorporating a semantic agentic layer enabled by the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication protocols, allowing context-aware decision making across real-time, near-real-time, and non-real-time control layers. Distributed cognitive agents deployed in rovers, landers, and lunar base stations implement wireless-aware coordination strategies, including delay-adaptive reasoning and bandwidth-aware semantic compression, while interacting with multiple MCP servers to reason over telemetry, locomotion planning, and mission constraints.