MIT and Ericsson are collaborating on two research projects that seek to help build a new network infrastructure needed to empower the truly revolutionary use cases the next generation of mobile networks will bring, announced Ericsson last week.
The new mobile network generations bring ultra-fast speed, low latency, and superb reliability to the end user. However large, feature rich networks are complex structures to manage for network operators. Ericsson is working to research cognitive networks, which rely on artificial intelligence (AI) to enable a secure, highly automized, data-driven network operation.
To improve the compute power, speed and energy efficiency of cognitive networks, Ericsson Research and the MIT Materials Research Laboratory are collaborating to research new designs in lithionic chips enabling neuromorphic computing, offering exponentially more energy efficient AI processing. This could enable fully cognitive networks with reduced operation complexity and energy consumption compared to today.
In addition to research on lithionics, Ericsson and the MIT Research Laboratory of Electronics (RLE) are collaborating on research of mobile networks that connect trillions of sensors and other “zero-energy” devices around us. Powering these devices in a cost-efficient way, possibly directly via a radio signal, is a significant technology challenge. The research by Ericsson and MIT RLE may show how devices can harvest energy from radio signals and other sources, as well as how systems can be designed to utilize this low power to accomplish simple tasks, including how a mobile network may be designed to connect and control these devices.
Anantha P. Chandrakasan, Dean of MIT’s School of Engineering
By combining our knowledge with Ericsson’s expertise in mobile technology, we aim to develop hardware that will power exciting new AI applications on the edge, and take significant strides in the next generation of mobile networks.
Magnus Frodigh, Head of Ericsson Research
Massive amounts of tiny IoT devices and AI-driven, cognitive networks are two drivers of the next leap forward. Working with the brilliant teams at MIT, we hope to develop the hardware that will make that possible.
