Huawei and Turkcell have jointly released a solution for Next Generation (NG) Wireless OSS. Latest test results show that the solution has greatly improved network Operation and Maintenance (O&M) efficiency via the customized WebUI and app-level fast upgrade based on microservice technology.
Towards the 5G era, operators face diverse challenges, such as complex network O&M, low resource efficiency, and difficult service experience assurance. NG Wireless OSS utilizes the latest technologies with microservices and AI, helping operators automate their network O&M and succeed in their digital transformation journey. The latest solution will provide the following benefits:
Scale-out capability for large-network management to realize “One Country, One System”
Fast Time-to-Market and high availability based on microservices to realize app-level independent upgrade
Programmable capability based on openness to realize customized O&M and closed-loop end-to-end workflow
Moving forward, Turkcell and Huawei will continue to innovate in joint workflow design, automatic system verification, and network capability openness as planned, and both parties are also determined to further cooperate and innovate in network O&M automation.
Ozgur Genc, Core Network Capabilities Director of Turkcell, said, “O&M automation is one of Turkcell’s core strategies for evolution to 5G. Turkcell will accelerate its exploration of O&M automation through continuous innovation with Huawei. In addition, Turkcell will continue to reshape its tool chain system to meet demands for future O&M automation.”
“The successful deployment of NG wireless OSS in Turkcell is a solid foundation for O&M automation,” said Lin Guixiao, President of Huawei Wireless Network SingleOSS Product Line.
With the new mission of NG Wireless OSS being to realize O&M automation from 5G, and to achieve autonomous driving networks, Huawei will continuously build automation capabilities based on the newly released MBB automation Engine (MAE). This will unleash network automation potential and accelerate full-scenario autonomous driving in mobile networks.
