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2018 North-American School of Information Theory

Texas A&M University College of Engineering

Information-theoretic perspective on massive multiple-access.

Yury Polyanksiy, MIT

The key expected innovation of the next generation of radio-access networks is
their ability to service orders of magnitude more active devices (the “Internet-of-Things”).
Current networks were designed focusing on the regime of relatively few simultaneously active users. The typical (and information-theoretically optimal) solution is to
orthogonalize degrees of freedom of different users via a centralized resource allocation.
This solution requires significant control-layer overhead, and, under machine-type communication, incurs unacceptable penalty on latency and energy
efficiency.

In this tutorial, I will survey the relevant classical results on MAC as well as discuss the novel formulations introduced by the IoT, namely defining the probability of error is per user instead of globally for all users, scaling the number of users proportional to blocklength and forcing
users to employ exactly the same codebook. A key conclusion is that there is an orders-of-magnitude gap between the energy-per-bit achievable
by the best (by prohibitively complex) MAC algorithm and popular practical solutions.
Our goal is to inspire the next generation of information theorists and coding theorists to close this gap.

Bio:
Yury Polyanskiy is an Associate Professor of Electrical Engineering and Computer Science and a member of LIDS at MIT.
Yury received M.S. degree in applied mathematics and physics from the Moscow Institute of Physics and Technology,
Moscow, Russia in 2005 and Ph.D. degree in electrical engineering from Princeton
University, Princeton, NJ in 2010. Currently, his research focuses on basic questions in information theory, error-correcting codes, wireless communication and fault-tolerant and defect-tolerant circuits.
Dr. Polyanskiy won the 2013 NSF CAREER award and 2011 IEEE Information Theory Society Paper Award.

Presentation slides

 

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