The rapid expansion of wireless technologies demands effective management of complex RAN for MIMO in 5G systems. Current architectures and RAN Intelligent Controllers (RICs) lack critical real-time data processing and physical layer functionalities, hindering MIMO advancements. We introduce BeamArmor5G, an open-source MIMO App development framework that addresses these gaps with comprehensive PHY layer capabilities, enabling detailed wireless channel measurement streaming from RAN to the controller. BeamArmor5G is implemented with srsRAN to empower open-source community researchers to advance beamforming, localization, and interference management, significantly enhancing network performance and enabling new 5G applications.

The adoption of MIMO technology in wireless networks enhances spectral efficiency and enables novel functionalities such as wireless sensing and localization. These functionalities can be enabled by Open-RAN architecture to provide high computation, memory, and data-driven inference through a RAN Intelligent Controller (RIC). However, existing RICs focus mainly on higher network layers and lack essential PHY layer functionalities for MIMO. We present MIMO-RIC, an open-source RAN intelligent controller tailored for MIMO applications. We enable the streaming of extensive 3D wireless channel measurements across antennas, subcarriers, and time, from RAN to MIMO-RIC to develop various MIMO apps like beamforming and localization. We implemented MIMO-RIC on the srsRAN open-source platform using ZeroMQ messaging system for efficient, low-latency communication. Our over-the-air experiment setup consisting of USRP radios and commercial user equipment demonstrates effective jammer monitoring, nulling, and user localization applications.

This demo showcases the mm-O-RAN testbed, integrating mmWave arrays with USRP and the OpenAirInterface (OAI) 5G stack. Our system integrates the mmWave array with synchronized Time Division Duplex (TDD) switching and fast beamforming capabilities, using GPIO triggers from the OAI stack. As the first full integration of a mmWave testbed with an OAI 5G stack, mm-O-RAN addresses key challenges in design and implementation, providing a versatile platform for research and experimentation for AI and signal processing algorithms to optimize end-end network performance.