Radio AI Design
About this role
Radio AI design is in product system department, which is responsible for next generation Radio system prepared for 6G with AI/ML technology enabling. This role is focused on the study of how to leverage AI/ML to improve performance and efficiency in different areas, including radio algorithms evolution, radio function and base band collaboration evolution, AI radio HW evolution and radio quality maintenance improvement. This role will take end to end responsibility from AI idea study to productization.
About PDU Radio
Product Development Unit Radio (PDU Radio) drives the end-to-end research and development of Ericsson’s radio products and solutions. PDU Radio is a global organization, within Development Unit Networks (DNEW), of approximately 4,000 engineers and developers collaborating across nine sites in Canada, China, and Sweden to drive Ericsson’s strategy of securing our ongoing market leadership in radio, taking a leadership position in 5G.
About Radio Products China
Radio Products China is end-to-end responsible for product development from F0 until maintenance of radio products developed in China. We are approximately 1,000 engineers and developers collaborating mainly between Beijing and Chengdu sites to drive Massive MIMO, Classic and Indoor radio technology leadership and product competitiveness in Hardware, Software and Enclosure areas through early concept study, product systemization, solution design, integration and verification, product introduction and maintenance. We are an R&D organization known of Execution excellence, Accountability mindset and Speak-up culture. We pursue our vision according to Ericsson’s strategy through continuous investing in People, securing world class Quality experience and delivering industry leading Energy efficient product towards customer value.
Responsibilities
The engineer of radio AI design:
· Research on the AI/ML application in communication industry, study AI impact to radio system and sub-systems in at least one of below different areas.
· Research on AI/ML impact to radio HW structure, design next generation of HW platform supported with AI enabling.
· Research on AI/ML for radio algorithms evolution to improvement radio system performance, design AI/ML enabling algorithms e.g. DPD, CFR, PIMC, Antena Calibration and Beamforming.
· Design AI/ML based radio function collaboration and energy efficiency system.
· Apply AI/ML to quality management, log analysis and customer field issue resolving.
