Tupl Agro y el Colegio Oficial de Ingenieros Técnicos Agrícolas de Málaga firman un acuerdo para poner a disposición de los colegiados un software de inteligencia artificial
2022-12-20 · Press Releases
Currently, regarding the tilt of the base station antenna, radio engineers perform various tunings and set the optimum angle while considering the radio conditions and the relations between multiple cells. Tupl RF Shaping performs deep reinforcement learning based on terminal location information and radio related data to calculate the optimal tilt angle. This will enable effective use of frequencies, improvement of radio conditions within cells, reduction of interference, and improvement of user quality.
This time, in collaboration with DOCOMO, we devised a new way to give rewards for reinforcement learning, conducted a trial to evaluate improvements in area coverage and capacity within the area, and confirmed the effects. This result is implemented in the same solution, and will be sold and deployed globally.
Mr. Masafumi Masuda, General Manager of Radio Access Network Development Department, NTT DOCOMO, INC. stated, “This time, two companies have achieved an excellent outcome in the trial of optimization of base stations’ antenna tilt settings. This outcome was obtained through leveraging the technical strengths of both companies, i.e., Tupl’s knowledge of network optimization employing the deep reinforcement learning and DOCOMO’s experience as a mobile network operator. We also consider this a useful achievement of our co-creation.”
Tupl CEO Petri Hautakangas said: “With this trial with NTT DOCOMO, we were able to further evolve our RF Shaping solution. Currently, many telecommunications carriers spend a great deal of effort and cost to adjust base station tilts. We hope this solution will improve the efficiency of processes and quality for operators around the world.”
Shinichi Kanno, head of Tupl's Asia-Pacific region and representative of Tupl Japan G.K., said as follows. “We believe that this trial with NTT DOCOMO is a big step towards the automation and development of radio optimization. Currently, cells and frequencies are extremely complex, and we believe that such solutions will be essential in order to optimally respond to ever-changing traffic.”
For more information about Tupl, please visit www.tupl.com.
Founded in 2014 by telecom, big data and AI experts, Tupl is pioneering the digital transformation of the telecom industry by automating network operations with AI. The company's AI engine, TuplOS, leverages machine learning and other technologies to accelerate the innovation cycle of network and customer care operations for wireless carriers in the United States, Japan, Mexico, and Europe.
Headquartered in Bellevue, Washington, USA, with offices in Spain, Mexico, and Japan, Tupl is rapidly expanding its global presence by 2022. For more information on Tupl, please visit https://www.tupl.com/
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