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Artificial Intelligence Applications in Open RAN

The evolution of mobile networks has witnessed a shift with the advent of Open RAN (Radio Access Network) solutions. Historically, traditional network architectures were characterized by proprietary, monolithic systems, and limiting flexibility.

Open RAN represents a paradigm shift in the mobile sector with an extended and disaggregated approach to network infrastructure. The concept gained momentum as a response to the desire for greater interoperability, vendor diversity, and cost efficiency.

This approach enables the decoupling of hardware and software components. Open RAN enables the deployment of adaptable systems that can keep pace with the advancements in wireless technology.

Open RAN Market Development 

Emerging Artificial Intelligence (AI) and Machine Learning (ML) innovations in Open RAN Massive MIMO (mMIMO) solutions will play a pivotal role in improving performance to match that of traditional RAN mMIMO, according to the latest worldwide market study by ABI Research.

While traditional RAN vendors currently dominate the mMIMO market, momentum for Open RAN is building as the technology matures, with pioneering deployments from operators like Rakuten and DISH.

"Advanced AI and ML techniques are poised to help close the performance gap by enhancing key capabilities such as beamforming and channel estimation," said Larbi Belkhit, research analyst at ABI Research.

According to the ABI assessment, integration of these models, likely in the Distributed Unit (DU), will be instrumental for Open RAN vendors to maximize spectrum efficiency.

Companies such as DeepSig are already demonstrating that AI-powered software can improve Open RAN mMIMO efficiency. Its OmniPHY solution leverages ML for improved channel estimation, beam optimization, and interference mitigation in 5G networks.

As AI/ML applications mature, such solutions applied to Open RAN mMIMO will boost performance and energy consumption closer to that of the current traditional RAN levels.

The integration of AI and ML techniques, along with other innovations in energy efficiency and GPU acceleration, will advance performance improvements similar to those in existing RAN networks.

"This will remove critical barriers to Open RAN adoption and pave the way for flexible, interoperable 5G deployments for network operators rather than reliance on radio network equipment from traditional vendors currently dominating the market, such as Ericsson, Huawei, and Nokia," Belkhit concludes.

These findings are from the ABI Research 5G Massive MIMO market developments study. It's part of their ongoing research based on extensive primary interviews, with in-depth analysis of market trends.

Outlook for AI Applications Growth in OpenRAN

That said, I've previously explored the historical roots of Open RAN, its evolution, and the driving forces behind its adoption. I believe more network applications will benefit from the flexibility and openness offered by this innovative approach, and its potential to revolutionize mobile networks.

After an eventful couple of years, Open RAN has helped mobile network providers overcome market disruptions such as the COVID-19 pandemic, geopolitical situations, and an energy crisis. Open RAN also gained interest among mobile vendors, semiconductor manufacturers, and public cloud providers.

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