3 Ways Nokia is Using Machine Learning in 5G Networks

Wireless carriers around the world are pushing to bring 5G service to their customers as quickly as possible, but the new radio access networks--which will rely on emerging technologies including millimeter waves and huge antenna arrays known as massive MIMO--will be a lot more complicated than what came before. Nokia is applying machine learning to some of the problems that result from this complexity, hoping that artificial intelligence can boost network performance and cut costs, Rajeev Agrawal said recently during a 5G summit at the Computex trade show in Taipei, Taiwan. Agrawal, who is in charge of Nokia's radio access network offerings, presented three possibilities for machine learning and 5G that Nokia has studied internally but not yet published in academic research papers. In a MIMO (multiple-input multiple-output) network, cellular base stations send and receive radio frequency signals in parallel through many more antennas than are normally used on a base station. This means the base station can transmit and receive more data, but these signals also interfere with one another.