AI/ML Wireless Technology Recognition Using Photonic-Electronic Neuromorphic Engine

Simultaneously, there's a burgeoning field of research exploring the integration of MIMO wireless signals with fiber-optic networks, resulting in a hybrid infrastructure that capitalizes on the strengths of both technologies. Specifically, Radio over Fiber (RoF) links between the Baseband Unit (BBU) and Remote Radio Head (RRH) offer advantages such as high bandwidth, low latency, and long-range connectivity. MIMO wireless technology complements this by extending network coverage, improving mobility support, and facilitating last-mile connectivity. Notably, analog RoF configurations centralize various signal processing functions, leading to cost reductions in remote antenna units.

Leveraging the potential synergy between MIMO wireless signals and RoF technology presents a promising opportunity to integrate edge neuromorphic computing with electronic-photonic integrated circuits (EPICs). Identifying suitable technologies at both the BBU and RRH levels is crucial for making informed spectrum management decisions. Ensuring compliance with the stringent requirements of 5G networks necessitates swift execution of signal detection in the fronthaul. Here, the utilization of photonic-electronic neuromorphic engine architectures proves essential, as they offer rapid and power efficient detection capabilities.