Robin.io and AirHop Communications announced a strategic partnership to provide solutions that deliver automated improvements in the performance of Open Radio Access Networks (Open RAN) and end-user quality of experience.
Robin and AirHop technologies are key enablers for Rakuten Mobile’s 4G/5G network in Japan as well as the Rakuten Communication Platform (RCP) delivering virtualization, standardization, optimization and automation of 5G Open RAN, leading to more cost efficiency, innovation and affordability.
Robin.io core technologies — Multi Cluster Automation Platform (MDCAP), Cloud Native Platform (CNP), and Cloud Native Storage (CNS) — will provide a cloud native infrastructure for onboarding network functions. The technologies also will deliver hyper-automation that orchestrates and manages the lifecycles of bare-metal infrastructures, third-party appliances, Virtual Network Functions (VNFs), Cloud-native Network Functions (CNFs) and services.
AirHop provides a suite of real-time network intelligence solutions delivering Radio Access Network (RAN) automation and performance optimization for coverage and capacity, network configuration, mobility optimization and network operations.
AirHop’s eSON solution is commercially hardened with large-scale deployments at Reliance Jio and Rakuten Mobile. eSON provides MNOs with deployment flexibility supporting optimization applications for disaggregated vRAN architectures as a pre-standard, near-real-time RAN Intelligent Controller (RIC) platform and as xApps/rApps on emerging near real-time and non-real-time RIC platforms based on O-RAN standards. eSON applications optimize performance across Rakuten Mobile’s end-to-end cloud native wireless network for macro cell, small cell and HetNet coverage use cases delivering improved spectral efficiency of the network, resulting in higher throughput and more capacity, reduced operational expenses through automated configuration and issue resolution, and dynamic balancing of user traffic across the network. eSON360 provides AI/ML based rApps across a broad spectrum of target RAN optimization use cases.
