PARTNER CONTENT: Interpretation of Next-generation Wireless OSS as Huawei Releases Wireless AI

On the eve of MWC 2018, Huawei released the next-generation wireless OSS solution that is designed to satisfy operators’ requirements on network O&M. By introducing cloud and AI technologies, Huawei aims at building a wireless OSS that enables network and service automation to support operators’ successful deployment of commercial use cases.

At the Twelfth Operator CTO Round-table Meeting held at MWC, network automation was the hottest topic of discussion. Attendees expressed their demands for network automation in the 5G era and reached a consensus on introducing AI and cloud technologies in mobile networks to accelerate the pace of network automation.

Adapting Network Operation to the 5G Era

  • A top-level design is a must for network O&M in the 5G era. Tracing back to the evolutionary progress of mobile networks, definition and standardization of O&M requirements in the 3G and 4G eras lag behind those of NEs. This causes obstacles for O&M feature implementation. In the 5G era, the complexity of O&M significantly increases and O&M is further coordinated with NEs. This means that the patch installation O&M mode is no longer applicable and must be replaced. A top-level design is required for defining network O&M requirements and standardization to ensure the maximum coordination of O&M and NEs.
  • Cloud & Wireless AI for the 5G dream of network Operation. In the 4G era, Huawei proposed the concept of a self-organizing network (SON). Will network self-organizing be realized in the 5G era? Although a definite answer has yet to be realized, cloud and AI technologies provide a strong sense of hope for the future. Cloud and AI technologies have been combined with IT O&M, generating new O&M concepts, such as DevOps and AIOps. However, this does not mean that network O&M in the 5G era can simply replicate the concepts of IT O&M. Wireless network O&M has unique characteristics, such as:
  • Distributed site deployment architecture
  • Scenario-specific mobile network environment and dynamic traffic
  • Controlled dependency of service experience on networks

On one hand, new ideas of IT O&M need to be introduced into next-generation O&M. On the other, cloud and AI technologies are best adapted to wireless network features. This will enable mobile networks to benefit from full automation.

Core 5G Business Competitiveness: Next-generation Wireless OSS

Before MWC 2018, a survey on 5G deployment challenges was conducted at the Huawei Pre-MWC Briefing in London. The survey results show that analysts generally believe that the deployment cost is one of the most significant challenges. In the 5G era, operators face a new digital market. Compared with the traditional MBB market, the industrial digital market expects slow and unstable revenue. Therefore, mobile networks must be flexible enough to implement fast service adaptation and low-cost incubation. In other words, operators must manipulate the cost structure to adapt to the development requirements of new 5G services. Only by improving the network automation level can we transform the cost structure and realize agile network O&M.

The Industry’s First Definition of the Next-generation Wireless OSS Based on Wireless AI

Unmanned vehicles of the highest caliber require no manual operation at all. In the field of network O&M, the industry is pursuing the realization of automatic running and maintenance of mobile networks. Generally, a connected vehicle has the following capabilities: automatic obstacle avoidance (based on machine vision), control (based on a digital brain), best driving experience (based on a digital platform), and intelligent and open interconnection.

Huawei highlights that the next-generation wireless OSS based on Wireless AI is recommended to have the following capabilities:

  • Site Automation to Simplify Device O&M
    This is a sensing technology, similar to that of the automatic obstacle avoidance capability of unmanned vehicles. In the 5G era, networking is ultra-dense with various distributed sites, and the number of site visits (especially that of senior technical engineers’ site visits) greatly influences network O&M costs. Many operators have stressed the necessity of site automation. Site automation can help realize hardware proactive monitoring, installation, configuration, and intelligent alarm association, minimizing site visits and O&M complexity.
  • Network Cognition to Maximize Network Resource Utilization
    This capability is comparable to unmanned vehicles’ control capability based on real-time scenarios. In the 5G era, the mobile brain enables cognitive, predictive, and self-learning capabilities to target network scenarios and traffic fluctuations. Multi-frequency and multi-RAT complex heterogeneous networks require more consideration for specific scenarios. For example, 5G Massive MIMO has more than 10000 combinations of cell coverage configurations due to the introduction of narrow beam technology. Therefore, the system must be able to dynamically adjust to coverage scenarios and traffic changes within just a few minutes. Driven by mobile big data and based on cognitive algorithms such as machine learning and deep learning, the network cognition can implement precise allocation of network resources with the support of high computing capabilities. This helps operators maximize resource and network usages.
  • Service Agility to Accelerate Operators’ Business Success
    Currently, most mainstream unmanned vehicles have abandoned mechanical drive systems and adopted digital electronic systems. In addition, electric vehicles provide better driving experience in terms of acceleration, silent mode, endurance and other features. In the 5G era, operators must attract a new growth curve for digital services, especially for that of sliced services. The traditional MBB market uses the Best Effort service assurance mechanism. In the digital market, Service Level Agreements (SLA) become a prerequisite for new service development. This will get O&M systems integrated into operators’ business flows, form a complete production system, and facilitate operators’ business successes.
  • Operation flexibility to Meet Differentiated Management Requirements:
    In case of traffic jams, unmanned vehicles connect to the intelligent transportation system through the Internet of Vehicles (IoV) and run orderly, greatly cutting travel time. Facing differentiated O&M management requirements in the 5G era, operators and developers can use data, features, and layered ecosystems to customize network O&M. With the convenient management integration function, the O&M system can be accessed to existing workflows and systems.

In 2018, Huawei Wireless Network Product Line will launch two core solutions based on the next-generation wireless OSS concept. One is the cloud-based U2020 and the other is the service-oriented agile mAOS O&M system driven by Wireless AI. These two solutions will help operators build network automation capabilities at the starting line of the 5G era. Mr. Zhou Yuefeng, Chief Marketing Officer of Huawei Wireless Solution, said that we are currently well on the way to reshaping the O&M experience. Next-generation wireless OSS based on Wireless AI can potentially help optimize the development of operators’ network and service automation to achieve new levels of commercial success in the 5G era.

In February, a cherry red Tesla car was successfully launched into space. The mission for us is similar. We must endeavor to turn a static network into a fully automated network, realize network self-running and self-maintenance in the 2020s, and thereby create additional space for operators to increase service innovation.